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SLURP! Spectroscopy of Liquids Using Robot Pre-Touch Sensing
|
https://ieeexplore.ieee.org/document/10161084/
|
[
"Nathaniel Hanson",
"Wesley Lewis",
"Kavya Puthuveetil",
"Donelle Furline",
"Akhil Padmanabha",
"Taşlan Padir",
"Zackory Erickson",
"Nathaniel Hanson",
"Wesley Lewis",
"Kavya Puthuveetil",
"Donelle Furline",
"Akhil Padmanabha",
"Taşlan Padir",
"Zackory Erickson"
] |
Liquids and granular media are pervasive throughout human environments. Their free-flowing nature causes people to constrain them into containers. We do so with thousands of different types of containers made out of different materials with varying sizes, shapes, and colors. In this work, we present a state-of-the-art sensing technique for robots to perceive what liquid is inside of an unknown con...
|
Tactile based robotic skills for cable routing operations
|
https://ieeexplore.ieee.org/document/10160729/
|
[
"Andrea Monguzzi",
"Martina Pelosi",
"Andrea Maria Zanchettin",
"Paolo Rocco",
"Andrea Monguzzi",
"Martina Pelosi",
"Andrea Maria Zanchettin",
"Paolo Rocco"
] |
This paper proposes a set of tactile based skills to perform robotic cable routing operations for deformable linear objects (DLOs) characterized by considerable stiffness and constrained at both ends. In particular, tactile data are exploited to reconstruct the shape of the grasped portion of the DLO and to estimate the future local one. This information is exploited to obtain a grasping configura...
|
Category-Level Global Camera Pose Estimation with Multi-Hypothesis Point Cloud Correspondences
|
https://ieeexplore.ieee.org/document/10161193/
|
[
"Jun–Jee Chao",
"Selim Engin",
"Nicolai Häni",
"Volkan Isler",
"Jun–Jee Chao",
"Selim Engin",
"Nicolai Häni",
"Volkan Isler"
] |
Correspondence search is an essential step in rigid point cloud registration algorithms. Most methods maintain a single correspondence at each step and gradually remove wrong correspondances. However, building one-to-one correspondence with hard assignments is extremely difficult, especially when matching two point clouds with many locally similar features. This paper proposes an optimization meth...
|
GSMR-CNN: An End-to-End Trainable Architecture for Grasping Target Objects from Multi-Object Scenes
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https://ieeexplore.ieee.org/document/10161009/
|
[
"Valerija Holomjova",
"Andrew J. Starkey",
"Pascal Meißner",
"Valerija Holomjova",
"Andrew J. Starkey",
"Pascal Meißner"
] |
We present an end-to-end trainable multi-task model that locates and retrieves target objects from multi-object scenes. The model is an extension of the Siamese Mask R-CNN, which combines the components of Siamese Neural Networks (SNNs) and Mask R-CNN for performing one-shot instance segmentation. The proposed network, called Grasping Siamese Mask R-CNN (GSMR-CNN), extends Siamese Mask R-CNN by ad...
|
3DSGrasp: 3D Shape-Completion for Robotic Grasp
|
https://ieeexplore.ieee.org/document/10160350/
|
[
"Seyed S. Mohammadi",
"Nuno F. Duarte",
"Dimitrios Dimou",
"Yiming Wang",
"Matteo Taiana",
"Pietro Morerio",
"Atabak Dehban",
"Plinio Moreno",
"Alexandre Bernardino",
"Alessio Del Bue",
"José Santos-Victor",
"Seyed S. Mohammadi",
"Nuno F. Duarte",
"Dimitrios Dimou",
"Yiming Wang",
"Matteo Taiana",
"Pietro Morerio",
"Atabak Dehban",
"Plinio Moreno",
"Alexandre Bernardino",
"Alessio Del Bue",
"José Santos-Victor"
] |
Real-world robotic grasping can be done robustly if a complete 3D Point Cloud Data (PCD) of an object is available. However, in practice, PCDs are often incomplete when objects are viewed from few and sparse viewpoints before the grasping action, leading to the generation of wrong or inaccurate grasp poses. We propose a novel grasping strategy, named 3DSGrasp, that predicts the missing geometry fr...
|
Goal-Conditioned Action Space Reduction for Deformable Object Manipulation
|
https://ieeexplore.ieee.org/document/10161541/
|
[
"Shengyin Wang",
"Rafael Papallas",
"Matteo Leonetti",
"Mehmet Dogar",
"Shengyin Wang",
"Rafael Papallas",
"Matteo Leonetti",
"Mehmet Dogar"
] |
Planning for deformable object manipulation has been a challenge for a long time in robotics due to its high computational cost. In this work, we propose to reduce this cost by reducing the number of pick points on a deformable object in the action space. We do this by identifying a small number of key particles that are sufficient as pick points to reach a given goal state. We find these key part...
|
MMRDN: Consistent Representation for Multi-View Manipulation Relationship Detection in Object-Stacked Scenes
|
https://ieeexplore.ieee.org/document/10161450/
|
[
"Han Wang",
"Jiayuan Zhang",
"Lipeng Wan",
"Xingyu Chen",
"Xuguang Lan",
"Nanning Zheng",
"Han Wang",
"Jiayuan Zhang",
"Lipeng Wan",
"Xingyu Chen",
"Xuguang Lan",
"Nanning Zheng"
] |
Manipulation relationship detection (MRD) aims to guide the robot to grasp objects in the right order, which is important to ensure the safety and reliability of grasping in object stacked scenes. Previous works infer manipulation relationship by deep neural network trained with data collected from a predefined view, which has limitation in visual dislocation in unstructured environments. Multi-vi...
|
SCARP: 3D Shape Completion in ARbitrary Poses for Improved Grasping
|
https://ieeexplore.ieee.org/document/10160365/
|
[
"Bipasha Sen",
"Aditya Agarwal",
"Gaurav Singh",
"Brojeshwar B.",
"Srinath Sridhar",
"Madhava Krishna",
"Bipasha Sen",
"Aditya Agarwal",
"Gaurav Singh",
"Brojeshwar B.",
"Srinath Sridhar",
"Madhava Krishna"
] |
Recovering full 3D shapes from partial observations is a challenging task that has been extensively addressed in the computer vision community. Many deep learning methods tackle this problem by training 3D shape generation networks to learn a prior over the full 3D shapes. In this training regime, the methods expect the inputs to be in a fixed canonical form, without which they fail to learn a val...
|
Category-level Shape Estimation for Densely Cluttered Objects
|
https://ieeexplore.ieee.org/document/10161221/
|
[
"Zhenyu Wu",
"Ziwei Wang",
"Jiwen Lu",
"Haibin Yan",
"Zhenyu Wu",
"Ziwei Wang",
"Jiwen Lu",
"Haibin Yan"
] |
Accurately estimating the shape of objects in dense clutters makes important contribution to robotic packing, because the optimal object arrangement requires the robot planner to acquire shape information of all existed objects. However, the objects for packing are usually piled in dense clutters with severe occlusion, and the object shape varies significantly across different instances for the sa...
|
Counter-Hypothetical Particle Filters for Single Object Pose Tracking
|
https://ieeexplore.ieee.org/document/10160625/
|
[
"Elizabeth A. Olson",
"Jana Pavlasek",
"Jasmine A. Berry",
"Odest Chadwicke Jenkins",
"Elizabeth A. Olson",
"Jana Pavlasek",
"Jasmine A. Berry",
"Odest Chadwicke Jenkins"
] |
Particle filtering is a common technique for six degree of freedom (6D) pose estimation due to its ability to tractably represent belief over object pose. However, the particle filter is prone to particle deprivation due to the high-dimensional nature of 6D pose. When particle deprivation occurs, it can cause mode collapse of the underlying belief distri-bution during importance sampling. If the r...
|
Reinforcement Learning Based Pushing and Grasping Objects from Ungraspable Poses
|
https://ieeexplore.ieee.org/document/10160491/
|
[
"Hao Zhang",
"Hongzhuo Liang",
"Lin Cong",
"Jianzhi Lyu",
"Long Zeng",
"Pingfa Feng",
"Jianwei Zhang",
"Hao Zhang",
"Hongzhuo Liang",
"Lin Cong",
"Jianzhi Lyu",
"Long Zeng",
"Pingfa Feng",
"Jianwei Zhang"
] |
Grasping an object when it is in an ungraspable pose is a challenging task, such as books or other large flat objects placed horizontally on a table. Inspired by human manipulation, we address this problem by pushing the object to the edge of the table and then grasping it from the hanging part. In this paper, we develop a model-free Deep Reinforcement Learning framework to synergize pushing and g...
|
Efficient Bimanual Handover and Rearrangement via Symmetry-Aware Actor-Critic Learning
|
https://ieeexplore.ieee.org/document/10160739/
|
[
"Yunfei Li",
"Chaoyi Pan",
"Huazhe Xu",
"Xiaolong Wang",
"Yi Wu",
"Yunfei Li",
"Chaoyi Pan",
"Huazhe Xu",
"Xiaolong Wang",
"Yi Wu"
] |
Bimanual manipulation is important for building intelligent robots that unlock richer skills than single arms. We consider a multi-object bimanual rearrangement task, where a reinforcement learning (RL) agent aims to jointly control two arms to rearrange these objects as fast as possible. Solving this task efficiently is challenging for an RL agent due to the requirement of discovering precise int...
|
EDO-Net: Learning Elastic Properties of Deformable Objects from Graph Dynamics
|
https://ieeexplore.ieee.org/document/10161234/
|
[
"Alberta Longhini",
"Marco Moletta",
"Alfredo Reichlin",
"Michael C. Welle",
"David Held",
"Zackory Erickson",
"Danica Kragic",
"Alberta Longhini",
"Marco Moletta",
"Alfredo Reichlin",
"Michael C. Welle",
"David Held",
"Zackory Erickson",
"Danica Kragic"
] |
We study the problem of learning graph dynamics of deformable objects that generalizes to unknown physical properties. Our key insight is to leverage a latent representation of elastic physical properties of cloth-like deformable objects that can be extracted, for example, from a pulling interaction. In this paper we propose EDO-Net (Elastic Deformable Object - Net), a model of graph dynamics trai...
|
Edge Grasp Network: A Graph-Based SE(3)-invariant Approach to Grasp Detection
|
https://ieeexplore.ieee.org/document/10160728/
|
[
"Haojie Huang",
"Dian Wang",
"Xupeng Zhu",
"Robin Walters",
"Robert Platt",
"Haojie Huang",
"Dian Wang",
"Xupeng Zhu",
"Robin Walters",
"Robert Platt"
] |
Given point cloud input, the problem of 6-DoF grasp pose detection is to identify a set of hand poses in SE(3) from which an object can be successfully grasped. This important problem has many practical applications. Here we propose a novel method and neural network model that enables better grasp success rates relative to what is available in the literature. The method takes standard point cloud ...
|
Learning Dexterous Manipulation from Exemplar Object Trajectories and Pre-Grasps
|
https://ieeexplore.ieee.org/document/10161147/
|
[
"Sudeep Dasari",
"Abhinav Gupta",
"Vikash Kumar",
"Sudeep Dasari",
"Abhinav Gupta",
"Vikash Kumar"
] |
Learning diverse dexterous manipulation behaviors with assorted objects remains an open grand challenge. While policy learning methods offer a powerful avenue to attack this problem, these approaches require extensive per-task engineering and algorithmic tuning. This paper seeks to escape these constraints, by developing a Pre-Grasp informed Dexterous Manipulation (PGDM) framework that generates d...
|
A Multi-Agent Approach for Adaptive Finger Cooperation in Learning-based In-Hand Manipulation
|
https://ieeexplore.ieee.org/document/10160909/
|
[
"Lingfeng Tao",
"Jiucai Zhang",
"Michael Bowman",
"Xiaoli Zhang",
"Lingfeng Tao",
"Jiucai Zhang",
"Michael Bowman",
"Xiaoli Zhang"
] |
In-hand manipulation is challenging for a multi-finger robotic hand due to its high degrees of freedom and complex interaction with the object. To enable in-hand manipulation, existing deep reinforcement learning-based approaches mainly focus on training a single robot-structure-specific policy through the centralized learning mechanism, lacking adaptability to changes like robot malfunction. To s...
|
Bimanual Rope Manipulation Skill Synthesis through Context Dependent Correction Policy Learning from Human Demonstration
|
https://ieeexplore.ieee.org/document/10160895/
|
[
"Baturhan Akbulut",
"Tuba Girgin",
"Arash Mehrabi",
"Minoru Asada",
"Emre Ugur",
"Erhan Oztop",
"Baturhan Akbulut",
"Tuba Girgin",
"Arash Mehrabi",
"Minoru Asada",
"Emre Ugur",
"Erhan Oztop"
] |
Learning from demonstration (LfD) with behavior cloning is attractive for its simplicity; however, compounding errors in long and complex skills can be a hindrance. Considering a target skill as a sequence of motor primitives is helpful in this respect. Then the requirement that a motor primitive ends in a state that allows the successful execution of the subsequent primitive must be met. In this ...
|
Sim-and-Real Reinforcement Learning for Manipulation: A Consensus-based Approach
|
https://ieeexplore.ieee.org/document/10161062/
|
[
"Wenxing Liu",
"Hanlin Niu",
"Wei Pan",
"Guido Herrmann",
"Joaquin Carrasco",
"Wenxing Liu",
"Hanlin Niu",
"Wei Pan",
"Guido Herrmann",
"Joaquin Carrasco"
] |
Sim-and-real training is a promising alternative to sim-to-real training for robot manipulations. However, the current sim-and-real training is neither efficient, i.e., slow con-vergence to the optimal policy, nor effective, i.e., sizeable real-world robot data. Given limited time and hardware budgets, the performance of sim-and-real training is not satisfactory. In this paper, we propose a Consen...
|
AutoBag: Learning to Open Plastic Bags and Insert Objects
|
https://ieeexplore.ieee.org/document/10161402/
|
[
"Lawrence Yunliang Chen",
"Baiyu Shi",
"Daniel Seita",
"Richard Cheng",
"Thomas Kollar",
"David Held",
"Ken Goldberg",
"Lawrence Yunliang Chen",
"Baiyu Shi",
"Daniel Seita",
"Richard Cheng",
"Thomas Kollar",
"David Held",
"Ken Goldberg"
] |
Thin plastic bags are ubiquitous in retail stores, healthcare, food handling, recycling, homes, and school lunchrooms. They are challenging both for perception (due to specularities and occlusions) and for manipulation (due to the dynamics of their 3D deformable structure). We formulate the task of “bagging:” manipulating common plastic shopping bags with two handles from an unstructured initial s...
|
Toward Fine Contact Interactions: Learning to Control Normal Contact Force with Limited Information
|
https://ieeexplore.ieee.org/document/10161224/
|
[
"Jinda Cui",
"Jiawei Xu",
"David Saldana",
"Jeff Trinkle",
"Jinda Cui",
"Jiawei Xu",
"David Saldana",
"Jeff Trinkle"
] |
Dexterous manipulation of objects through fine control of physical contacts is essential for many important tasks of daily living. A fundamental ability underlying fine contact control is compliant control, i.e., controlling the contact forces while moving. For robots, the most widely explored approaches heavily depend on models of manipulated objects and expensive sensors to gather contact locati...
|
Ditto in the House: Building Articulation Models of Indoor Scenes through Interactive Perception
|
https://ieeexplore.ieee.org/document/10161431/
|
[
"Cheng-Chun Hsu",
"Zhenyu Jiang",
"Yuke Zhu",
"Cheng-Chun Hsu",
"Zhenyu Jiang",
"Yuke Zhu"
] |
Virtualizing the physical world into virtual models has been a critical technique for robot navigation and planning in the real world. To foster manipulation with articulated objects in everyday life, this work explores building articulation models of indoor scenes through a robot's purposeful inter-actions in these scenes. Prior work on articulation reasoning primarily focuses on siloed objects o...
|
Zero-Shot Transfer of Haptics-Based Object Insertion Policies
|
https://ieeexplore.ieee.org/document/10160346/
|
[
"Samarth Brahmbhatt",
"Ankur Deka",
"Andrew Spielberg",
"Matthias Müller",
"Samarth Brahmbhatt",
"Ankur Deka",
"Andrew Spielberg",
"Matthias Müller"
] |
Humans naturally exploit haptic feedback during contact-rich tasks like loading a dishwasher or stocking a bookshelf. Current robotic systems focus on avoiding unexpected contact, often relying on strategically placed environment sensors. Recently, contact-exploiting manipulation policies have been trained in simulation and deployed on real robots. However, they require some form of real-world ada...
|
Moment-Based Kalman Filter: Nonlinear Kalman Filtering with Exact Moment Propagation
|
https://ieeexplore.ieee.org/document/10160945/
|
[
"Yutaka Shimizu",
"Ashkan Jasour",
"Maani Ghaffari",
"Shinpei Kato",
"Yutaka Shimizu",
"Ashkan Jasour",
"Maani Ghaffari",
"Shinpei Kato"
] |
This paper develops a new nonlinear filter, called Moment-based Kalman Filter (MKF), using the exact moment propagation method. Existing state estimation methods use linearization techniques or sampling points to compute approximate values of moments. However, moment propagation of probability distributions of random variables through nonlinear process and measurement models play a key role in the...
|
Unsupervised Quality Prediction for Improved Single-Frame and Weighted Sequential Visual Place Recognition
|
https://ieeexplore.ieee.org/document/10160679/
|
[
"Helen Carson",
"Jason J. Ford",
"Michael Milford",
"Helen Carson",
"Jason J. Ford",
"Michael Milford"
] |
While substantial progress has been made in the absolute performance of localization and Visual Place Recognition (VPR) techniques, it is becoming increasingly clear from translating these systems into applications that other capabilities like integrity and predictability are just as important, especially for safety- or operationally-critical autonomous systems. In this research we present a new, ...
|
Towards Consistent Batch State Estimation Using a Time-Correlated Measurement Noise Model
|
https://ieeexplore.ieee.org/document/10160257/
|
[
"David J. Yoon",
"Timothy D. Barfoot",
"David J. Yoon",
"Timothy D. Barfoot"
] |
In this paper, we present an algorithm for learning time-correlated measurement covariances for application in batch state estimation. We parameterize the inverse measurement covariance matrix to be block-banded, which conveniently factorizes and results in a computationally efficient approach for correlating measurements across the entire trajectory. We train our covariance model through supervis...
|
A Probabilistic Framework for Visual Localization in Ambiguous Scenes
|
https://ieeexplore.ieee.org/document/10160466/
|
[
"Fereidoon Zangeneh",
"Leonard Bruns",
"Amit Dekel",
"Alessandro Pieropan",
"Patric Jensfelt",
"Fereidoon Zangeneh",
"Leonard Bruns",
"Amit Dekel",
"Alessandro Pieropan",
"Patric Jensfelt"
] |
Visual localization allows autonomous robots to relocalize when losing track of their pose by matching their current observation with past ones. However, ambiguous scenes pose a challenge for such systems, as repetitive structures can be viewed from many distinct, equally likely camera poses, which means it is not sufficient to produce a single best pose hypothesis. In this work, we propose a prob...
|
RoLM: Radar on LiDAR Map Localization
|
https://ieeexplore.ieee.org/document/10161203/
|
[
"Yukai Ma",
"Xiangrui Zhao",
"Han Li",
"Yaqing Gu",
"Xiaolei Lang",
"Yong Liu",
"Yukai Ma",
"Xiangrui Zhao",
"Han Li",
"Yaqing Gu",
"Xiaolei Lang",
"Yong Liu"
] |
Multi-sensor fusion-based localization technology has achieved high accuracy in autonomous systems. How to improve the robustness is the main challenge at present. The most commonly used LiDAR and camera are weather-sensitive, while the FMCW radar has strong adaptability but suffers from noise and ghost effects. In this paper, we propose a heterogeneous localization method of Radar on LiDAR Map (R...
|
Direct LiDAR-Inertial Odometry: Lightweight LIO with Continuous-Time Motion Correction
|
https://ieeexplore.ieee.org/document/10160508/
|
[
"Kenny Chen",
"Ryan Nemiroff",
"Brett T. Lopez",
"Kenny Chen",
"Ryan Nemiroff",
"Brett T. Lopez"
] |
Aggressive motions from agile flights or traversing irregular terrain induce motion distortion in LiDAR scans that can degrade state estimation and mapping. Some methods exist to mitigate this effect, but they are still too simplistic or computationally costly for resource-constrained mobile robots. To this end, this paper presents Direct LiDAR-Inertial Odometry (DLIO), a lightweight LiDAR-inertia...
|
Large-Scale Radar Localization using Online Public Maps
|
https://ieeexplore.ieee.org/document/10160730/
|
[
"Ziyang Hong",
"Yvan Petillot",
"Kaicheng Zhang",
"Shida Xu",
"Sen Wang",
"Ziyang Hong",
"Yvan Petillot",
"Kaicheng Zhang",
"Shida Xu",
"Sen Wang"
] |
In this paper, we propose using online public maps, e.g., OpenStreetMap (OSM), for large-scale radar-based localization without needing a prior sensing map. This can potentially extend the localization system to anywhere worldwide without building, saving, or maintaining a sensing map, as long as an online public map covers the operating area. Existing methods using OSM only use route network or s...
|
Continuous-Time LiDAR-Inertial-Vehicle Odometry Method with Lateral Acceleration Constraint
|
https://ieeexplore.ieee.org/document/10161093/
|
[
"Bin He",
"Weichen Dai",
"Zeyu Wan",
"Hong Zhang",
"Yu Zhang",
"Bin He",
"Weichen Dai",
"Zeyu Wan",
"Hong Zhang",
"Yu Zhang"
] |
In this paper, we propose a continuous-time-based LiDAR-inertial-vehicle odometry method, which can tightly fuse the data from Light Detection And Ranging (LiDAR), inertial measurement units (IMU), and vehicle measurements. The lateral acceleration constraint is further added to trajectory estimation to make the estimated trajectory follow the motion characteristics of vehicles. In addition, since...
|
Cross-Modal Monocular Localization in Prior LiDAR Maps Utilizing Semantic Consistency
|
https://ieeexplore.ieee.org/document/10160810/
|
[
"Chi Zhang",
"Hengwang Zhao",
"Chunxiang Wang",
"Xuanlai Tang",
"Ming Yang",
"Chi Zhang",
"Hengwang Zhao",
"Chunxiang Wang",
"Xuanlai Tang",
"Ming Yang"
] |
Visual localization for mobile robots and intelligent vehicles in prior LiDAR maps can achieve high accuracy and low cost. However, algorithms for finding the cross-modal correspondences between images and LiDAR map points are not yet stable. In this paper, we propose a monocular visual localization system in prior LiDAR maps, which is based on the cross-modal registration to optimize the camera p...
|
Multi-State Tightly-Coupled EKF-Based Radar-Inertial Odometry With Persistent Landmarks
|
https://ieeexplore.ieee.org/document/10160482/
|
[
"Jan Michalczyk",
"Roland Jung",
"Christian Brommer",
"Stephan Weiss",
"Jan Michalczyk",
"Roland Jung",
"Christian Brommer",
"Stephan Weiss"
] |
In this paper, we present a Radar-Inertial Odometry (RIO) approach that utilizes performance improving modules, enhanced for the sparse and noisy radar signals, from the vision community in order to estimate the full 6DoF pose and 3D velocity of a robot in an unprepared environment. Our method leverages a multi-state approach in which we make use of several past robot poses and trails of measureme...
|
Loc-NeRF: Monte Carlo Localization using Neural Radiance Fields
|
https://ieeexplore.ieee.org/document/10160782/
|
[
"Dominic Maggio",
"Marcus Abate",
"Jingnan Shi",
"Courtney Mario",
"Luca Carlone",
"Dominic Maggio",
"Marcus Abate",
"Jingnan Shi",
"Courtney Mario",
"Luca Carlone"
] |
We present Loc-NeRF, a real-time vision-based robot localization approach that combines Monte Carlo localization and Neural Radiance Fields (NeRF). Our system uses a pre-trained NeRF model as the map of an environment and can localize itself in real-time using an RGB camera as the only exteroceptive sensor onboard the robot. While neural radiance fields have seen significant applications for visua...
|
RoSS: Rotation-induced Aliasing for Audio Source Separation
|
https://ieeexplore.ieee.org/document/10161106/
|
[
"Hyungjoo Seo",
"Sahil Bhandary Karnoor",
"Romit Roy Choudhury",
"Hyungjoo Seo",
"Sahil Bhandary Karnoor",
"Romit Roy Choudhury"
] |
This paper considers the problem of audio source separation, where the goal is to isolate a target audio signal (say Alice's speech) from a mixture of multiple interfering signals (e.g., when many people are talking). This problem has gained renewed interest mainly due to the significant growth in voice-controlled devices, including robots in homes, offices, and other public facilities. Although a...
|
L-C*: Visual-inertial Loose Coupling for Resilient and Lightweight Direct Visual Localization
|
https://ieeexplore.ieee.org/document/10161443/
|
[
"Shuji Oishi",
"Kenji Koide",
"Masashi Yokozuka",
"Atsuhiko Banno",
"Shuji Oishi",
"Kenji Koide",
"Masashi Yokozuka",
"Atsuhiko Banno"
] |
This study presents a framework, L-C*, for resilient and lightweight direct visual localization, employing a loosely coupled fusion of visual and inertial data. Unlike indirect methods, direct visual localization facilitates accurate pose estimation on general color three-dimensional maps that are not tailored for visual localization. However, it suffers from temporal localization failures and hig...
|
GRM: Gradient Rectification Module for Visual Place Retrieval
|
https://ieeexplore.ieee.org/document/10160994/
|
[
"Boshu Lei",
"Wenjie Ding",
"Limeng Qiao",
"Xi Qiu",
"Boshu Lei",
"Wenjie Ding",
"Limeng Qiao",
"Xi Qiu"
] |
Visual place retrieval aims to search images in the database that depict similar places as the query image. However, global descriptors encoded by the network usually fall into a low dimensional principal space, which is harmful to the retrieval performance. We first analyze the cause of this phenomenon, pointing out that it is due to degraded distribution of the gradients of descriptors. Then, we...
|
DytanVO: Joint Refinement of Visual Odometry and Motion Segmentation in Dynamic Environments
|
https://ieeexplore.ieee.org/document/10161306/
|
[
"Shihao Shen",
"Yilin Cai",
"Wenshan Wang",
"Sebastian Scherer",
"Shihao Shen",
"Yilin Cai",
"Wenshan Wang",
"Sebastian Scherer"
] |
Learning-based visual odometry (VO) algorithms achieve remarkable performance on common static scenes, benefiting from high-capacity models and massive annotated data, but tend to fail in dynamic, populated environments. Semantic segmentation is largely used to discard dynamic associations before estimating camera motions but at the cost of discarding static features and is hard to scale up to uns...
|
NOCaL: Calibration-Free Semi-Supervised Learning of Odometry and Camera Intrinsics
|
https://ieeexplore.ieee.org/document/10160663/
|
[
"Ryan Griffiths",
"Jack Naylor",
"Donald G. Dansereau",
"Ryan Griffiths",
"Jack Naylor",
"Donald G. Dansereau"
] |
There are a multitude of emerging imaging technologies that could benefit robotics. However the need for bespoke models, calibration and low-level processing represents a key barrier to their adoption. In this work we present NOCaL, Neural Odometry and Calibration using Light fields, a semi-supervised learning architecture capable of interpreting previously unseen cameras without calibration. NOCa...
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Efficient View Path Planning for Autonomous Implicit Reconstruction
|
https://ieeexplore.ieee.org/document/10160793/
|
[
"Jing Zeng",
"Yanxu Li",
"Yunlong Ran",
"Shuo Li",
"Fei Gao",
"Lincheng Li",
"Shibo He",
"Jiming Chen",
"Qi Ye",
"Jing Zeng",
"Yanxu Li",
"Yunlong Ran",
"Shuo Li",
"Fei Gao",
"Lincheng Li",
"Shibo He",
"Jiming Chen",
"Qi Ye"
] |
Implicit neural representations have shown promising potential for 3D scene reconstruction. Recent work applies it to autonomous 3D reconstruction by learning information gain for view path planning. Effective as it is, the computation of the information gain is expensive, and compared with that using volumetric representations, collision checking using the implicit representation for a 3D point i...
|
Lighthouses and Global Graph Stabilization: Active SLAM for Low-compute, Narrow-FoV Robots
|
https://ieeexplore.ieee.org/document/10160381/
|
[
"Mohit Deshpande",
"Richard Kim",
"Dhruva Kumar",
"Jong Jin Park",
"Jim Zamiska",
"Mohit Deshpande",
"Richard Kim",
"Dhruva Kumar",
"Jong Jin Park",
"Jim Zamiska"
] |
Autonomous exploration to build a map of an unknown environment is a fundamental robotics problem. However, the quality of the map directly influences the quality of subsequent robot operation. Instability in a simultaneous localization and mapping (SLAM) system can lead to poor-quality maps and subsequent navigation failures during or after exploration. This becomes particularly noticeable in con...
|
ExAug: Robot-Conditioned Navigation Policies via Geometric Experience Augmentation
|
https://ieeexplore.ieee.org/document/10160761/
|
[
"Noriaki Hirose",
"Dhruv Shah",
"Ajay Sridhar",
"Sergey Levine",
"Noriaki Hirose",
"Dhruv Shah",
"Ajay Sridhar",
"Sergey Levine"
] |
Machine learning techniques rely on large and diverse datasets for generalization. Computer vision, natural language processing, and other applications can often reuse public datasets to train many different models. However, due to differences in physical configurations, it is challenging to leverage public datasets for training robotic control policies on new robot platforms or for new tasks. In ...
|
Multi-Object Navigation in real environments using hybrid policies
|
https://ieeexplore.ieee.org/document/10161030/
|
[
"Assem Sadek",
"Guillaume Bono",
"Boris Chidlovskii",
"Atilla Baskurt",
"Christian Wolf",
"Assem Sadek",
"Guillaume Bono",
"Boris Chidlovskii",
"Atilla Baskurt",
"Christian Wolf"
] |
Navigation has been classically solved in robotics through the combination of SLAM and planning. More recently, beyond waypoint planning, problems involving significant components of (visual) high-level reasoning have been explored in simulated environments, mostly addressed with large-scale machine learning, in particular RL, offline-RL or imitation learning. These methods require the agent to le...
|
AeriaLPiPS: A Local Planner for Aerial Vehicles with Geometric Collision Checking
|
https://ieeexplore.ieee.org/document/10160852/
|
[
"Justin S. Smith",
"Patricio Vela",
"Justin S. Smith",
"Patricio Vela"
] |
Real-time navigation in non-trivial environments by micro aerial vehicles (MAVs) predominantly relies on modelling the MAV with idealized geometry, such as a sphere. Simplified, conservative representations increase the likelihood of a planner failing to identify valid paths. That likelihood increases the more a robot's geometry differs from the idealized version. Few current approaches consider t...
|
Frontier Semantic Exploration for Visual Target Navigation
|
https://ieeexplore.ieee.org/document/10161059/
|
[
"Bangguo Yu",
"Hamidreza Kasaei",
"Ming Cao",
"Bangguo Yu",
"Hamidreza Kasaei",
"Ming Cao"
] |
This work focuses on the problem of visual target navigation, which is very important for autonomous robots as it is closely related to high-level tasks. To find a special object in unknown environments, classical and learning-based approaches are fundamental components of navigation that have been investigated thoroughly in the past. However, due to the difficulty in the representation of complic...
|
VINet: Visual and Inertial-based Terrain Classification and Adaptive Navigation over Unknown Terrain
|
https://ieeexplore.ieee.org/document/10161251/
|
[
"Tianrui Guan",
"Ruitao Song",
"Zhixian Ye",
"Liangjun Zhang",
"Tianrui Guan",
"Ruitao Song",
"Zhixian Ye",
"Liangjun Zhang"
] |
We present a visual and inertial-based terrain classification network (VINet) for robotic navigation over different traversable surfaces. We use a novel navigation-based labeling scheme for terrain classification and generalization on unknown surfaces. Our proposed perception method and adaptive scheduling control framework can make predictions according to terrain navigation properties and lead t...
|
Ground then Navigate: Language-guided Navigation in Dynamic Scenes
|
https://ieeexplore.ieee.org/document/10160614/
|
[
"Kanishk Jain",
"Varun Chhangani",
"Amogh Tiwari",
"K. Madhava Krishna",
"Vineet Gandhi",
"Kanishk Jain",
"Varun Chhangani",
"Amogh Tiwari",
"K. Madhava Krishna",
"Vineet Gandhi"
] |
We investigate the Vision-and-Language Navigation (VLN) problem in the context of autonomous driving in outdoor settings. We solve the problem by explicitly grounding the navigable regions corresponding to the textual command. At each timestamp, the model predicts a segmentation mask corresponding to the intermediate or the final navigable region. Our work contrasts with existing efforts in VLN, w...
|
3-Dimensional Sonic Phase-invariant Echo Localization
|
https://ieeexplore.ieee.org/document/10161199/
|
[
"Christopher Hahne",
"Christopher Hahne"
] |
Parallax and Time-of-Flight (ToF) are often regarded as complementary in robotic vision where various light and weather conditions remain challenges for advanced camera-based 3-Dimensional (3-D) reconstruction. To this end, this paper establishes Parallax among Corresponding Echoes (PaCE) to triangulate acoustic ToF pulses from arbitrary sensor positions in 3-D space for the first time. This is ac...
|
Calibration and Uncertainty Characterization for Ultra-Wideband Two-Way-Ranging Measurements
|
https://ieeexplore.ieee.org/document/10160769/
|
[
"Mohammed Ayman Shalaby",
"Charles Champagne Cossette",
"James Richard Forbes",
"Jerome Le Ny",
"Mohammed Ayman Shalaby",
"Charles Champagne Cossette",
"James Richard Forbes",
"Jerome Le Ny"
] |
Ultra-Wideband (UWB) systems are becoming increasingly popular for indoor localization, where range measurements are obtained by measuring the time-of-flight of radio signals. However, the range measurements typically suffer from a systematic error or bias that must be corrected for high-accuracy localization. In this paper, a ranging protocol is proposed alongside a robust and scalable antenna-de...
|
High Resolution Point Clouds from mmWave Radar
|
https://ieeexplore.ieee.org/document/10161429/
|
[
"Akarsh Prabhakara",
"Tao Jin",
"Arnav Das",
"Gantavya Bhatt",
"Lilly Kumari",
"Elahe Soltanaghai",
"Jeff Bilmes",
"Swarun Kumar",
"Anthony Rowe",
"Akarsh Prabhakara",
"Tao Jin",
"Arnav Das",
"Gantavya Bhatt",
"Lilly Kumari",
"Elahe Soltanaghai",
"Jeff Bilmes",
"Swarun Kumar",
"Anthony Rowe"
] |
This paper explores a machine learning approach on data from a single-chip mmWave radar for generating high resolution point clouds – a key sensing primitive for robotic applications such as mapping, odometry and localization. Unlike lidar and vision-based systems, mmWave radar can operate in harsh environments and see through occlusions like smoke, fog, and dust. Unfortunately, current mmWave pro...
|
Pyramid Learnable Tokens for 3D LiDAR Place Recognition
|
https://ieeexplore.ieee.org/document/10161523/
|
[
"Congcong Wen",
"Hao Huang",
"Yu-Shen Liu",
"Yi Fang",
"Congcong Wen",
"Hao Huang",
"Yu-Shen Liu",
"Yi Fang"
] |
3D LiDAR place recognition plays a vital role in various robot applications' including robotic navigation, autonomous driving, and simultaneous localization and mapping. However, most previous studies evaluated their models on accumulated 2D scans instead of real-world 3D LiDAR scans with a larger number of points, which limits the application in real scenarios. To address this limitation, we prop...
|
A Decoupled and Linear Framework for Global Outlier Rejection over Planar Pose Graph
|
https://ieeexplore.ieee.org/document/10160540/
|
[
"Tianyue Wu",
"Fei Gao",
"Tianyue Wu",
"Fei Gao"
] |
We propose a robust framework for planar pose graph optimization contaminated by loop closure outliers. Our framework rejects outliers by first decoupling the robust PGO problem wrapped by a Truncated Least Squares kernel into two subproblems. Then, the framework introduces a linear angle representation to rewrite the first subproblem that is originally formulated in rotation matrices. The framewo...
|
Robust Incremental Smoothing and Mapping (riSAM)
|
https://ieeexplore.ieee.org/document/10161438/
|
[
"Daniel McGann",
"John G. Rogers",
"Michael Kaess",
"Daniel McGann",
"John G. Rogers",
"Michael Kaess"
] |
This paper presents a method for robust optimization for online incremental Simultaneous Localization and Mapping (SLAM). Due to the NP-Hardness of data association in the presence of perceptual aliasing, tractable (approximate) approaches to data association will produce erroneous measurements. We require SLAM back-ends that can converge to accurate solutions in the presence of outlier measuremen...
|
Real-Time Simultaneous Localization and Mapping with LiDAR Intensity
|
https://ieeexplore.ieee.org/document/10160713/
|
[
"Wenqiang Du",
"Giovanni Beltrame",
"Wenqiang Du",
"Giovanni Beltrame"
] |
We propose a novel real-time LiDAR intensity image-based simultaneous localization and mapping method, which addresses the geometry degeneracy problem in un-structured environments. Traditional LiDAR-based front-end odometry mostly relies on geometric features such as points, lines and planes. A lack of these features in the environment can lead to the failure of the entire odometry system. To avo...
|
iMODE:Real-Time Incremental Monocular Dense Mapping Using Neural Field
|
https://ieeexplore.ieee.org/document/10161538/
|
[
"Hidenobu Matsuki",
"Edgar Sucar",
"Tristan Laidow",
"Kentaro Wada",
"Raluca Scona",
"Andrew J. Davison",
"Hidenobu Matsuki",
"Edgar Sucar",
"Tristan Laidow",
"Kentaro Wada",
"Raluca Scona",
"Andrew J. Davison"
] |
We present a novel real-time dense and semantic neural field mapping system that uses only monocular images as input. Our scene representation is a dense continuous radiance field represented by a Multi-Layer Perceptron (MLP), trained from scratch in real-time. We build on high-performance sparse visual SLAM and use camera poses and sparse keypoint depths as supervision alongside RGB keyframes. Si...
|
Probabilistic Uncertainty Quantification of Prediction Models with Application to Visual Localization
|
https://ieeexplore.ieee.org/document/10160298/
|
[
"Junan Chen",
"Josephine Monica",
"Wei-Lun Chao",
"Mark Campbell",
"Junan Chen",
"Josephine Monica",
"Wei-Lun Chao",
"Mark Campbell"
] |
The uncertainty quantification of prediction models (e.g., neural networks) is crucial for their adoption in many robotics applications. This is arguably as important as making accurate predictions, especially for safety-critical applications such as self-driving cars. This paper proposes our approach to uncertainty quantification in the context of visual localization for autonomous driving, where...
|
Extrinsic calibration for highly accurate trajectories reconstruction
|
https://ieeexplore.ieee.org/document/10160505/
|
[
"Maxime Vaidis",
"William Dubois",
"Alexandre Guénette",
"Johann Laconte",
"Vladimír Kubelka",
"François Pomerleau",
"Maxime Vaidis",
"William Dubois",
"Alexandre Guénette",
"Johann Laconte",
"Vladimír Kubelka",
"François Pomerleau"
] |
In the context of robotics, accurate ground-truth positioning is the cornerstone for the development of mapping and localization algorithms. In outdoor environments and over long distances, total stations provide accurate and precise measurements, that are unaffected by the usual factors that deteriorate the accuracy of Global Navigation Satellite System (GNSS). While a single robotic total statio...
|
Cerberus: Low-Drift Visual-Inertial-Leg Odometry For Agile Locomotion
|
https://ieeexplore.ieee.org/document/10160486/
|
[
"Shuo Yang",
"Zixin Zhang",
"Zhengyu Fu",
"Zachary Manchester",
"Shuo Yang",
"Zixin Zhang",
"Zhengyu Fu",
"Zachary Manchester"
] |
We present an open-source Visual-Inertial-Leg Odometry (VILO) state estimation solution for legged robots, called Cerberus, which precisely estimates position on various terrains in real-time using a set of standard sensors, including stereo cameras, IMU, joint encoders, and contact sensors. In addition to estimating robot states, we perform online kinematic parameter calibration and outlier rejec...
|
Ensembles of Compact, Region-specific & Regularized Spiking Neural Networks for Scalable Place Recognition
|
https://ieeexplore.ieee.org/document/10160749/
|
[
"Somayeh Hussaini",
"Michael Milford",
"Tobias Fischer",
"Somayeh Hussaini",
"Michael Milford",
"Tobias Fischer"
] |
Spiking neural networks have significant potential utility in robotics due to their high energy efficiency on specialized hardware, but proof-of-concept implementations have not yet typically achieved competitive performance or capability with conventional approaches. In this paper, we tackle one of the key practical challenges of scalability by introducing a novel modular ensemble network approac...
|
Demonstration-Guided Reinforcement Learning with Efficient Exploration for Task Automation of Surgical Robot
|
https://ieeexplore.ieee.org/document/10160327/
|
[
"Tao Huang",
"Kai Chen",
"Bin Li",
"Yun-Hui Liu",
"Qi Dou",
"Tao Huang",
"Kai Chen",
"Bin Li",
"Yun-Hui Liu",
"Qi Dou"
] |
Task automation of surgical robot has the potentials to improve surgical efficiency. Recent reinforcement learning (RL) based approaches provide scalable solutions to surgical automation, but typically require extensive data collection to solve a task if no prior knowledge is given. This issue is known as the exploration challenge, which can be alleviated by providing expert demonstrations to an R...
|
Dual Robot Collaborative System for Autonomous Venous Access Based on Ultrasound and Bioimpedance Sensing Technology
|
https://ieeexplore.ieee.org/document/10160848/
|
[
"Maria Koskinopoulou",
"Alperen Acemoglu",
"Veronica Penza",
"Leonardo S. Mattos",
"Maria Koskinopoulou",
"Alperen Acemoglu",
"Veronica Penza",
"Leonardo S. Mattos"
] |
Accurate needle insertion is an important task in many medical procedures. This paper studies the case of an autonomous needle insertion system for central venous access, which is a risky and challenging procedure involving the simultaneous manipulation of an ultrasound probe and of a catheterization needle. The goal of this medical operation is to provide access to a deep central vein, which is a...
|
Vitreoretinal Surgical Robotic System with Autonomous Orbital Manipulation using Vector-Field Inequalities
|
https://ieeexplore.ieee.org/document/10160795/
|
[
"Yuki Koyama",
"Murilo M. Marinho",
"Kanako Harada",
"Yuki Koyama",
"Murilo M. Marinho",
"Kanako Harada"
] |
Vitreoretinal surgery pertains to the treatment of delicate tissues on the fundus of the eye using thin instruments. Surgeons frequently rotate the eye during surgery, which is called orbital manipulation, to observe regions around the fundus without moving the patient. In this paper, we propose the autonomous orbital manipulation of the eye in robot-assisted vitreoretinal surgery with our tele-op...
|
Autonomous Needle Navigation in Retinal Microsurgery: Evaluation in ex vivo Porcine Eyes
|
https://ieeexplore.ieee.org/document/10161151/
|
[
"Peiyao Zhang",
"Ji Woong Kim",
"Peter Gehlbach",
"Iulian Iordachita",
"Marin Kobilarov",
"Peiyao Zhang",
"Ji Woong Kim",
"Peter Gehlbach",
"Iulian Iordachita",
"Marin Kobilarov"
] |
Important challenges in retinal microsurgery in-clude prolonged operating time, inadequate force feedback, and poor depth perception due to a constrained top-down view of the surgery. The introduction of robot-assisted technology could potentially deal with such challenges and improve the surgeon's performance. Motivated by such challenges, this work develops a strategy for autonomous needle navig...
|
Dynamic Modeling and Identification of a Robotic Intracardiac Echo Catheter
|
https://ieeexplore.ieee.org/document/10160319/
|
[
"Mohammad Salehizadeh",
"Filipe Pedrosa",
"Harmanpreet Bassan",
"Rajni Patel",
"Jayender Jagadeesan",
"Mohammad Salehizadeh",
"Filipe Pedrosa",
"Harmanpreet Bassan",
"Rajni Patel",
"Jayender Jagadeesan"
] |
Catheter-based cardiac ablation is the preferred method of treating atrial fibrillation. Conventionally, the catheter is navigated in the heart using X-ray fluoroscopy imaging and an electroanatomical map. Although successful, these imaging modalities do not provide real-time feedback on the quality of lesions created, which in turn could lead to recurrence of arrhythmia. Intracardiac echo (ICE) c...
|
Modeling of a Robotic Transcatheter Delivery System
|
https://ieeexplore.ieee.org/document/10161486/
|
[
"Namrata U. Nayar",
"Ronghuai Qi",
"Jaydev P. Desai",
"Namrata U. Nayar",
"Ronghuai Qi",
"Jaydev P. Desai"
] |
Intracardiac transcatheter systems guided by advanced imaging modalities are gaining popularity in treating mitral regurgitation in non-surgical candidates. Robotically steerable transcatheter systems must use model-based control strategies to ensure safer and more effective transcatheter procedures with less trauma while using smaller control gains. In this paper, a 4-DoF robotically steerable te...
|
A Handheld Hydraulic Cardiac Catheter with Omnidirectional Manipulator and Touch Sensing
|
https://ieeexplore.ieee.org/document/10161196/
|
[
"Chi Cong Nguyen",
"James Davies",
"Mai Thanh Thai",
"Trung Thien Hoang",
"Phuoc Thien Phan",
"Kefan Zhu",
"Dang Bao Nhi Tran",
"Van Anh Ho",
"Hung Manh La",
"Hoang-Phuong Phan",
"Nigel H. Lovell",
"Thanh Nho Do",
"Chi Cong Nguyen",
"James Davies",
"Mai Thanh Thai",
"Trung Thien Hoang",
"Phuoc Thien Phan",
"Kefan Zhu",
"Dang Bao Nhi Tran",
"Van Anh Ho",
"Hung Manh La",
"Hoang-Phuong Phan",
"Nigel H. Lovell",
"Thanh Nho Do"
] |
Atrial fibrillation (AF) is mostly treated via robotic catheter-based cardiac ablation procedures. Over the last few decades, cables or tendon mechanisms are at the core of available cardiac catheters. Despite advances, the use of cables often results in considerable force loss, nonlinear hysteresis, and control challenges. Most catheters are not equipped with force sensing, which increases the ri...
|
Optimized Design and Analysis of Active Propeller-driven Capsule Endoscopic Robot for Gastric Examination
|
https://ieeexplore.ieee.org/document/10161057/
|
[
"Yi Zhang",
"Weihao Wang",
"Wende Ke",
"Chengzhi Hu",
"Yi Zhang",
"Weihao Wang",
"Wende Ke",
"Chengzhi Hu"
] |
Capsule endoscopic robot holds great promise for the early diagnosis of gastrointestinal diseases without causing discomfort to patients. However, currently available active capsule endoscopic robots suffer from issues such as complex structure, poor mobility, large size, and high cost, which have hindered their widespread adoption and resulted in a lower screening rate for gastrointestinal diseas...
|
QuadMag: A Mobile-Coil System With Enhanced Magnetic Actuation Efficiency and Dexterity
|
https://ieeexplore.ieee.org/document/10161290/
|
[
"Lidong Yang",
"Moqiu Zhang",
"Zhengxin Yang",
"Haojin Yang",
"Li Zhang",
"Lidong Yang",
"Moqiu Zhang",
"Zhengxin Yang",
"Haojin Yang",
"Li Zhang"
] |
Magnetic field is a favorable power source for actuation and control of micro-/nanorobots. To overcome the fast decay of magnetic field for large-workspace microrobotic actuation, mobile field source-based systems have been proposed. In this work, we report a new mobile-coil system, i.e., QuadMag. It consists of four electromagnetic coils, whose motion is actuated by a parallel mechanism. Compared...
|
Evaluating the Feasibility of Magnetic Tools for the Minimum Dynamic Requirements of Microneurosurgery
|
https://ieeexplore.ieee.org/document/10160840/
|
[
"Cameron Forbrigger",
"Erik Fredin",
"Eric Diller",
"Cameron Forbrigger",
"Erik Fredin",
"Eric Diller"
] |
Neurosurgery could benefit from robot-assisted minimally invasive approaches, but existing robot tools are insufficiently small and compact. Magnetic actuation is an attractive approach to medical robotics because it allows small, modular serial mechanisms to be remotely actuated. Despite these advantages, magnetic actuation is relatively weak compared to alternative actuation methods. In this pap...
|
A Novel Concentric Tube Steerable Drilling Robot for Minimally Invasive Treatment of Spinal Tumors Using Cavity and U-shape Drilling Techniques
|
https://ieeexplore.ieee.org/document/10160814/
|
[
"Susheela Sharma",
"Ji H. Park",
"Jordan P. Amadio",
"Mohsen Khadem",
"Farshid Alambeigi",
"Susheela Sharma",
"Ji H. Park",
"Jordan P. Amadio",
"Mohsen Khadem",
"Farshid Alambeigi"
] |
In this paper, we present the design, fabrication, and evaluation of a novel flexible, yet structurally strong, Concentric Tube Steerable Drilling Robot (CT-SDR) to improve minimally invasive treatment of spinal tumors. Inspired by concentric tube robots, the proposed two degree-of-freedom (DoF) CT-SDR, for the first time, not only allows a surgeon to intuitively and quickly drill smooth planar an...
|
Magnetic Ball Chain Robots for Endoluminal Interventions
|
https://ieeexplore.ieee.org/document/10160695/
|
[
"Giovanni Pittiglio",
"Margherita Mencattelli",
"Pierre E. Dupont",
"Giovanni Pittiglio",
"Margherita Mencattelli",
"Pierre E. Dupont"
] |
This paper introduces a novel class of hyperredun-dant robots comprised of chains of permanently magnetized spheres enclosed in a cylindrical polymer skin. With their shape controlled using an externally-applied magnetic field, the spherical joints of these robots enable them to bend to very small radii of curvature. These robots can be used as steerable tips for endoluminal instruments. A kinemat...
|
Robotic Navigation Autonomy for Subretinal Injection via Intelligent Real-Time Virtual iOCT Volume Slicing
|
https://ieeexplore.ieee.org/document/10160372/
|
[
"Shervin Dehghani",
"Michael Sommersperger",
"Peiyao Zhang",
"Alejandro Martin-Gomez",
"Benjamin Busam",
"Peter Gehlbach",
"Nassir Navab",
"M. Ali Nasseri",
"Iulian Iordachita",
"Shervin Dehghani",
"Michael Sommersperger",
"Peiyao Zhang",
"Alejandro Martin-Gomez",
"Benjamin Busam",
"Peter Gehlbach",
"Nassir Navab",
"M. Ali Nasseri",
"Iulian Iordachita"
] |
In the last decade, various robotic platforms have been introduced that could support delicate retinal surgeries. Concurrently, to provide semantic understanding of the surgical area, recent advances have enabled microscope-integrated intraoperative Optical Coherent Tomography (iOCT) with high-resolution 3D imaging at near video rate. The combination of robotics and semantic understanding enables ...
|
3D Reconstruction of Tibia and Fibula using One General Model and Two X-ray Images
|
https://ieeexplore.ieee.org/document/10161467/
|
[
"Kai Pan",
"Shuai Zhang",
"Liang Zhao",
"Shoudong Huang",
"Yanhao Zhang",
"Hua Wang",
"Qi Luo",
"Kai Pan",
"Shuai Zhang",
"Liang Zhao",
"Shoudong Huang",
"Yanhao Zhang",
"Hua Wang",
"Qi Luo"
] |
The 3D reconstruction of patient specific bone models plays a crucial role in orthopaedic surgery for clinical evaluation, surgical planning and precise implant design or selection. This paper considers the problem of reconstructing a patient-specific 3D tibia and fibula model from only two 2D X-ray images and one 3D general model segmented from the lower leg CT scans of one randomly selected pati...
|
Semantic-SuPer: A Semantic-aware Surgical Perception Framework for Endoscopic Tissue Identification, Reconstruction, and Tracking
|
https://ieeexplore.ieee.org/document/10160746/
|
[
"Shan Lin",
"Albert J. Miao",
"Jingpei Lu",
"Shunkai Yu",
"Zih-Yun Chiu",
"Florian Richter",
"Michael C. Yip",
"Shan Lin",
"Albert J. Miao",
"Jingpei Lu",
"Shunkai Yu",
"Zih-Yun Chiu",
"Florian Richter",
"Michael C. Yip"
] |
Accurate and robust tracking and reconstruction of the surgical scene is a critical enabling technology toward autonomous robotic surgery. Existing algorithms for 3D perception in surgery mainly rely on geometric information, while we propose to also leverage semantic information inferred from the endoscopic video using image segmentation algorithms. In this paper, we present a novel, comprehensiv...
|
Suture Thread Spline Reconstruction from Endoscopic Images for Robotic Surgery with Reliability-driven Keypoint Detection
|
https://ieeexplore.ieee.org/document/10161539/
|
[
"Neelay Joglekar",
"Fei Liu",
"Ryan Orosco",
"Michael Yip",
"Neelay Joglekar",
"Fei Liu",
"Ryan Orosco",
"Michael Yip"
] |
Automating the process of manipulating and delivering sutures during robotic surgery is a prominent problem at the frontier of surgical robotics, as automating this task can significantly reduce surgeons' fatigue during tele-operated surgery and allow them to spend more time addressing higher-level clinical decision making. Accomplishing autonomous suturing and suture manipulation in the real worl...
|
CDFI: Cross Domain Feature Interaction for Robust Bronchi Lumen Detection
|
https://ieeexplore.ieee.org/document/10160402/
|
[
"Jiasheng Xu",
"Tianyi Zhang",
"Yangqian Wu",
"Jie Yang",
"Guang–Zhong Yang",
"Yun Gu",
"Jiasheng Xu",
"Tianyi Zhang",
"Yangqian Wu",
"Jie Yang",
"Guang–Zhong Yang",
"Yun Gu"
] |
Endobronchial intervention is increasingly used as a minimally invasive means for the treatment of pulmonary diseases. In order to reduce the difficulty of manipulation in complex airway networks, robust lumen detection is essential for intraoperative guidance. However, these methods are sensitive to visual artifacts which are inevitable during the surgery. In this work, a cross domain feature int...
|
Real-Time Constrained 6D Object-Pose Tracking of An In-Hand Suture Needle for Minimally Invasive Robotic Surgery
|
https://ieeexplore.ieee.org/document/10161291/
|
[
"Zih-Yun Chiu",
"Florian Richter",
"Michael C. Yip",
"Zih-Yun Chiu",
"Florian Richter",
"Michael C. Yip"
] |
Autonomous suturing has been a long-sought-after goal for surgical robotics. Outside of staged environments, accurate localization of suture needles is a critical foundation for automating various suture needle manipulation tasks in the real world. When localizing a needle held by a gripper, previous work usually tracks them separately without considering their relationship. Because of the signifi...
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Exploring Robot-Assisted Optical Coherence Elastography for Surgical Palpation
|
https://ieeexplore.ieee.org/document/10160456/
|
[
"Yeonhee Chang",
"Elan Z. Ahronovich",
"Nabil Simaan",
"Cheol Song",
"Yeonhee Chang",
"Elan Z. Ahronovich",
"Nabil Simaan",
"Cheol Song"
] |
Optical Coherence Elastography (OCE) is a method that discerns local tissue stiffness using optical information. This method has recently been explored for laryngeal cancer tumor margin detection but has not been widely deployed clinically. Part of the challenge hindering such clinical deployment is the need for controlled high-precision mechanical probing of the tissue. This paper explores the co...
|
Locate before Segment: Topology-guided Retinal Layer Segmentation in Optical Coherence Tomography Images
|
https://ieeexplore.ieee.org/document/10160300/
|
[
"Ye Lu",
"Yutian Shen",
"Xiaohan Xing",
"Max Q.-H. Meng",
"Ye Lu",
"Yutian Shen",
"Xiaohan Xing",
"Max Q.-H. Meng"
] |
Optical Coherence Tomography (OCT) is a non-invasive imaging technique that is instrumental in retinal disease diagnosis and treatment. Segmentation of retinal layers in OCT is an essential step, but remains challenging for common pixel-wise segmentation methods usually fail to obtain the correct layer topology. To tackle this challenge, we propose a novel Locate-to-Segment (L2S) framework to prov...
|
Visual Tracking of Needle Tip in 2D Ultrasound based on Global Features in a Siamese Architecture
|
https://ieeexplore.ieee.org/document/10160822/
|
[
"Wanquan Yan",
"Qingpeng Ding",
"Jianghua Chen",
"Kim Yan",
"Raymond Shing-Yan Tang",
"Shing Shin Cheng",
"Wanquan Yan",
"Qingpeng Ding",
"Jianghua Chen",
"Kim Yan",
"Raymond Shing-Yan Tang",
"Shing Shin Cheng"
] |
Ultrasound (US) is widely used in image-guided needle procedures. Correctly tracking the needle tip position in US images during the procedure plays an important role in improving the needle targeting accuracy and patient safety. This paper presents a leaning-based visual tracking network with a Siamese architecture, which makes full use of the attention mechanism to explore the potential of globa...
|
Model-Based Pose Estimation of Steerable Catheters under Bi-Plane Image Feedback
|
https://ieeexplore.ieee.org/document/10161314/
|
[
"Jared Lawson",
"Rohan Chitale",
"Nabil Simaan",
"Jared Lawson",
"Rohan Chitale",
"Nabil Simaan"
] |
Small catheters undergo significant torsional deflections during endovascular interventions. A key challenge in enabling robot control of these catheters is the estimation of their bending planes. This paper considers approaches for estimating these bending planes based on bi-plane image feedback. The proposed approaches attempt to minimize error between either the direct (position-based) or insta...
|
Pose Quality Prediction for Vision Guided Robotic Shoulder Arthroplasty
|
https://ieeexplore.ieee.org/document/10161123/
|
[
"Morgan Windsor",
"Jing Peng",
"Ashish Gupta",
"Peter Pivonka",
"Michael J Milford",
"Morgan Windsor",
"Jing Peng",
"Ashish Gupta",
"Peter Pivonka",
"Michael J Milford"
] |
Surgical assistive robots offer the potential for drastically improved patient outcomes through more accurate, more repeatable surgical procedures like shoulder arthroplasty operations. Existing robotic systems typically rely on optical marker tracking and require invasive marker attachment for localization, complicating the surgical workflow and patient recovery. But moving towards a markerless s...
|
Image Segmentation for Continuum Robots from a Kinematic Prior
|
https://ieeexplore.ieee.org/document/10161229/
|
[
"Connor M. Watson",
"Anna B. Nguyen",
"Tania K. Morimoto",
"Connor M. Watson",
"Anna B. Nguyen",
"Tania K. Morimoto"
] |
In this work, we address the problem of robust segmentation of a continuum robot from images without the need for training data or markers. We present a method that leverages information about the kinematics of these robots to produce an estimate of the robot shape, which is refined through optimization over global image statistics. Our approach can be straightforwardly applied to any continuum ro...
|
Robust Collaborative 3D Object Detection in Presence of Pose Errors
|
https://ieeexplore.ieee.org/document/10160546/
|
[
"Yifan Lu",
"Quanhao Li",
"Baoan Liu",
"Mehrdad Dianati",
"Chen Feng",
"Siheng Chen",
"Yanfeng Wang",
"Yifan Lu",
"Quanhao Li",
"Baoan Liu",
"Mehrdad Dianati",
"Chen Feng",
"Siheng Chen",
"Yanfeng Wang"
] |
Collaborative 3D object detection exploits information exchange among multiple agents to enhance accuracy of object detection in presence of sensor impairments such as occlusion. However, in practice, pose estimation errors due to imperfect localization would cause spatial message misalignment and significantly reduce the performance of collaboration. To alleviate adverse impacts of pose errors, w...
|
Joint Semi-Supervised and Active Learning via 3D Consistency for 3D Object Detection
|
https://ieeexplore.ieee.org/document/10160433/
|
[
"Sihwan Hwang",
"Sanmin Kim",
"Youngseok Kim",
"Dongsuk Kum",
"Sihwan Hwang",
"Sanmin Kim",
"Youngseok Kim",
"Dongsuk Kum"
] |
Autonomous driving powered by deep learning requires large-scale, high-quality training data from diverse driving environments to operate effectively worldwide. However, collecting and annotating such data is costly and time-consuming. To address this challenge, active learning methods have been explored to select the most informative data samples for training. Nevertheless, most existing methods ...
|
StereoVoxelNet: Real-Time Obstacle Detection Based on Occupancy Voxels from a Stereo Camera Using Deep Neural Networks
|
https://ieeexplore.ieee.org/document/10160924/
|
[
"Hongyu Li",
"Zhengang Li",
"Neşet Ünver Akmandor",
"Huaizu Jiang",
"Yanzhi Wang",
"Taşkın Padır",
"Hongyu Li",
"Zhengang Li",
"Neşet Ünver Akmandor",
"Huaizu Jiang",
"Yanzhi Wang",
"Taşkın Padır"
] |
Obstacle detection is a safety-critical problem in robot navigation, where stereo matching is a popular vision-based approach. While deep neural networks have shown impressive results in computer vision, most of the previous obstacle detection works only leverage traditional stereo matching techniques to meet the computational constraints for real-time feedback. This paper proposes a computational...
|
Perceiving Unseen 3D Objects by Poking the Objects
|
https://ieeexplore.ieee.org/document/10160338/
|
[
"Linghao Chen",
"Yunzhou Song",
"Hujun Bao",
"Xiaowei Zhou",
"Linghao Chen",
"Yunzhou Song",
"Hujun Bao",
"Xiaowei Zhou"
] |
We present a novel approach to interactive 3D object perception for robots. Unlike previous perception algorithms that rely on known object models or a large amount of annotated training data, we propose a poking-based approach that automatically discovers and reconstructs 3D objects. The poking process not only enables the robot to discover unseen 3D objects but also produces multi-view observati...
|
MonoPGC: Monocular 3D Object Detection with Pixel Geometry Contexts
|
https://ieeexplore.ieee.org/document/10161442/
|
[
"Zizhang Wu",
"Yuanzhu Gan",
"Lei Wang",
"Guilian Chen",
"Jian Pu",
"Zizhang Wu",
"Yuanzhu Gan",
"Lei Wang",
"Guilian Chen",
"Jian Pu"
] |
Monocular 3D object detection reveals an economical but challenging task in autonomous driving. Recently center-based monocular methods have developed rapidly with a great trade-off between speed and accuracy, where they usually depend on the object center's depth estimation via 2D features. However, the visual semantic features without sufficient pixel geometry information, may affect the perform...
|
CrossDTR: Cross-view and Depth-guided Transformers for 3D Object Detection
|
https://ieeexplore.ieee.org/document/10161451/
|
[
"Ching-Yu Tseng",
"Yi-Rong Chen",
"Hsin-Ying Lee",
"Tsung-Han Wu",
"Wen-Chin Chen",
"Winston H. Hsu",
"Ching-Yu Tseng",
"Yi-Rong Chen",
"Hsin-Ying Lee",
"Tsung-Han Wu",
"Wen-Chin Chen",
"Winston H. Hsu"
] |
To achieve accurate 3D object detection at a low cost for autonomous driving, many multi-camera methods have been proposed and solved the occlusion problem of monocular approaches. However, due to the lack of accurate estimated depth, existing multi-camera methods often generate multiple bounding boxes along a ray of depth direction for difficult small objects such as pedestrians, resulting in an ...
|
DOTIE - Detecting Objects through Temporal Isolation of Events using a Spiking Architecture
|
https://ieeexplore.ieee.org/document/10161164/
|
[
"Manish Nagaraj",
"Chamika Mihiranga Liyanagedera",
"Kaushik Roy",
"Manish Nagaraj",
"Chamika Mihiranga Liyanagedera",
"Kaushik Roy"
] |
Vision-based autonomous navigation systems rely on fast and accurate object detection algorithms to avoid obstacles. Algorithms and sensors designed for such systems need to be computationally efficient, due to the limited energy of the hardware used for deployment. Biologically inspired event cameras are a good candidate as a vision sensor for such systems due to their speed, energy efficiency, a...
|
CEAFFOD: Cross-Ensemble Attention-based Feature Fusion Architecture Towards a Robust and Real-time UAV-based Object Detection in Complex Scenarios
|
https://ieeexplore.ieee.org/document/10161287/
|
[
"Ahmed Elhagry",
"Hang Dai",
"Abdulmotaleb El Saddik",
"Wail Gueaieb",
"Giulia De Masi",
"Ahmed Elhagry",
"Hang Dai",
"Abdulmotaleb El Saddik",
"Wail Gueaieb",
"Giulia De Masi"
] |
Deploying object detectors in embedded devices such as unmanned aerial vehicles (UAVs) comes with many challenges. This is due to both the UAV itself having low embedded resources in terms of computation and memory, and also due to the nature of the captured visual data with the variations in objects' scale, orientation, density, viewpoint, distribution, shape, context and others. It is crucial fo...
|
Test-time Domain Adaptation for Monocular Depth Estimation
|
https://ieeexplore.ieee.org/document/10161304/
|
[
"Zhi Li",
"Shaoshuai Shi",
"Bernt Schiele",
"Dengxin Dai",
"Zhi Li",
"Shaoshuai Shi",
"Bernt Schiele",
"Dengxin Dai"
] |
Test-time domain adaptation, i.e. adapting source-pretrained models to the test data on-the-fly in a source-free, unsupervised manner, is a highly practical yet very challenging task. Due to the domain gap between source and target data, inference quality on the target domain can drop drastically especially in terms of absolute scale of depth. In addition, unsupervised adaptation can degrade the m...
|
TODE-Trans: Transparent Object Depth Estimation with Transformer
|
https://ieeexplore.ieee.org/document/10160537/
|
[
"Kang Chen",
"Shaochen Wang",
"Beihao Xia",
"Dongxu Li",
"Zhen Kan",
"Bin Li",
"Kang Chen",
"Shaochen Wang",
"Beihao Xia",
"Dongxu Li",
"Zhen Kan",
"Bin Li"
] |
Transparent objects are widely used in industrial automation and daily life. However, robust visual recognition and perception of transparent objects have always been a major challenge. Currently, most commercial-grade depth cameras are still not good at sensing the surfaces of transparent objects due to the refraction and reflection of light. In this work, we present a transformer-based transpare...
|
Learning Depth Completion of Transparent Objects using Augmented Unpaired Data
|
https://ieeexplore.ieee.org/document/10160619/
|
[
"Floris Erich",
"Bruno Leme",
"Noriaki Ando",
"Ryo Hanai",
"Yukiyasu Domae",
"Floris Erich",
"Bruno Leme",
"Noriaki Ando",
"Ryo Hanai",
"Yukiyasu Domae"
] |
We propose a technique for depth completion of transparent objects using augmented data captured directly from real environments with complicated geometry. Using cyclic adversarial learning we train translators to convert between painted versions of the objects and their real transparent counterpart. The translators are trained on unpaired data, hence datasets can be created rapidly and without an...
|
Lightweight Monocular Depth Estimation via Token-Sharing Transformer
|
https://ieeexplore.ieee.org/document/10160566/
|
[
"Dong-Jae Lee",
"Jae Young Lee",
"Hyunguk Shon",
"Eojindl Yi",
"Yeong-Hun Park",
"Sung-Sik Cho",
"Junmo Kim",
"Dong-Jae Lee",
"Jae Young Lee",
"Hyunguk Shon",
"Eojindl Yi",
"Yeong-Hun Park",
"Sung-Sik Cho",
"Junmo Kim"
] |
Depth estimation is an important task in various robotics systems and applications. In mobile robotics systems, monocular depth estimation is desirable since a single RGB camera can be deployable at a low cost and compact size. Due to its significant and growing needs, many lightweight monocular depth estimation networks have been proposed for mobile robotics systems. While most lightweight monocu...
|
Improved Event-Based Dense Depth Estimation via Optical Flow Compensation
|
https://ieeexplore.ieee.org/document/10160605/
|
[
"Dianxi Shi",
"Luoxi Jing",
"Ruihao Li",
"Zhe Liu",
"Lin Wang",
"Huachi Xu",
"Yi Zhang",
"Dianxi Shi",
"Luoxi Jing",
"Ruihao Li",
"Zhe Liu",
"Lin Wang",
"Huachi Xu",
"Yi Zhang"
] |
Event cameras have the potential to overcome the limitations of classical computer vision in real-world applications. Depth estimation is a crucial step for high-level robotics tasks and has attracted much attention from the community. In this paper, we propose an event-based dense depth estimation architecture, Mixed-EF2DNet, which firstly predicts inter-grid optical flow to compensate for lost t...
|
TTCDist: Fast Distance Estimation From an Active Monocular Camera Using Time-to-Contact
|
https://ieeexplore.ieee.org/document/10160683/
|
[
"Levi Burner",
"Nitin J. Sanket",
"Cornelia Fermüller",
"Yiannis Aloimonos",
"Levi Burner",
"Nitin J. Sanket",
"Cornelia Fermüller",
"Yiannis Aloimonos"
] |
Distance estimation from vision is fundamental for a myriad of robotic applications such as navigation, manipu-lation, and planning. Inspired by the mammal's visual system, which gazes at specific objects, we develop two novel constraints relating time-to-contact, acceleration, and distance that we call the $\tau$ -constraint and $\Phi$ -constraint. They allow an active (moving) camera to estimate...
|
STEPS: Joint Self-supervised Nighttime Image Enhancement and Depth Estimation
|
https://ieeexplore.ieee.org/document/10160708/
|
[
"Yupeng Zheng",
"Chengliang Zhong",
"Pengfei Li",
"Huan-ang Gao",
"Yuhang Zheng",
"Bu Jin",
"Ling Wang",
"Hao Zhao",
"Guyue Zhou",
"Qichao Zhang",
"Dongbin Zhao",
"Yupeng Zheng",
"Chengliang Zhong",
"Pengfei Li",
"Huan-ang Gao",
"Yuhang Zheng",
"Bu Jin",
"Ling Wang",
"Hao Zhao",
"Guyue Zhou",
"Qichao Zhang",
"Dongbin Zhao"
] |
Self-supervised depth estimation draws a lot of attention recently as it can promote the 3D sensing capa-bilities of self-driving vehicles. However, it intrinsically relies upon the photometric consistency assumption, which hardly holds during nighttime. Although various supervised night-time image enhancement methods have been proposed, their generalization performance in challenging driving scen...
|
FG-Depth: Flow-Guided Unsupervised Monocular Depth Estimation
|
https://ieeexplore.ieee.org/document/10160534/
|
[
"Junyu Zhu",
"Lina Liu",
"Yong Liu",
"Wanlong Li",
"Feng Wen",
"Hongbo Zhang",
"Junyu Zhu",
"Lina Liu",
"Yong Liu",
"Wanlong Li",
"Feng Wen",
"Hongbo Zhang"
] |
The great potential of unsupervised monocular depth estimation has been demonstrated by many works due to low annotation cost and impressive accuracy comparable to supervised methods. To further improve the performance, recent works mainly focus on designing more complex network structures and exploiting extra supervised information, e.g., semantic segmentation. These methods optimize the models b...
|
Light-Weight Pointcloud Representation with Sparse Gaussian Process
|
https://ieeexplore.ieee.org/document/10161111/
|
[
"Mahmoud Ali",
"Lantao Liu",
"Mahmoud Ali",
"Lantao Liu"
] |
This paper presents a framework to represent high-fidelity pointcloud sensor observations for efficient communication and storage. The proposed approach exploits Sparse Gaussian Process to encode pointcloud into a compact form. Our approach represents both the free space and the occupied space using only one model (one 2D Sparse Gaussian Process) instead of the existing two-model framework (two 3D...
|
Test-Time Synthetic-to-Real Adaptive Depth Estimation
|
https://ieeexplore.ieee.org/document/10160773/
|
[
"Eojindl Yi",
"Junmo Kim",
"Eojindl Yi",
"Junmo Kim"
] |
Is it possible for a synthetic to realistic domain adapted neural network in single image depth estimation to truly generalize on real world data? The resultant, adapted model will only generalize on the realistic domain dataset, which only reflects a small portion of the true, real world. As a result, the network still has to cope with the potential danger of domain shift between the realistic do...
|
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