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IEEE International Conference on robotics and Automation (ICRA)

作者： Junming Zhang Manikandasriram Srinivasan Ramanagopal Ram Vasudevan Matthew Johnson-Roberson Department of Electrical Engineering and Computer Science University of Michigan Ann Arbor MI USA Robotics Program University of Michigan Ann Arbor MI USA Department of Mechanical Engineering University of Michigan Ann Arbor MI USA Department of Naval Architecture and Marine Engineering University of Michigan Ann Arbor MI USA

ISBN: (数字)9781728173955

ISBN: (纸本)9781728173962

An accurate depth map of the environment is critical to the safe operation of autonomous robots and vehicles. Currently, either light detection and ranging (LIDAR) or stereo matching algorithms are used to acquire such depth information. However, a high-resolution LIDAR is expensive and produces sparse depth map at large range; stereo matching algorithms are able to generate denser depth maps but are typically less accurate than LIDAR at long range. This paper combines these approaches together to generate high-quality dense depth maps. Unlike previous approaches that are trained using ground-truth labels, the proposed model adopts a self-supervised training process. Experiments show that the proposed method is able to generate high-quality dense depth maps and performs robustly even with low-resolution inputs. This shows the potential to reduce the cost by using LIDARs with lower resolution in concert with stereo systems while maintaining high resolution.

关键词： Laser radar Task analysis Training Feature extraction Estimation Convolution Correlation

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Learning to Estimate Centers of Mass of Arbitrary Objects

Learning to Estimate Centers of Mass of Arbitrary Objects

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2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Sean McGovern Huitan Mao Jing Xiao Robotics Engineering Program Worcester Polytechnic Institute Department of Computer Science University of North Carolina at Charlotte

This paper introduces a reinforcement learning algorithm with robot manipulation to learn an arbitrary object's center of mass whose physical material composition is unknown. Robot learning is through manipulation of the object in a sequence of actions. The effectiveness of the algorithm is demonstrated in simulation to locate the centers of mass of rocks with complex shapes, with even or uneven mass distributions, and confirmed by vertically stacking the rocks along their learned centers of mass both in simulation and in real experiments.

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Collaborative robotics Toolkit (CRTK): Open Software Framework for Surgical robotics Research

Collaborative Robotics Toolkit (CRTK): Open Software Framewo...

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IEEE International Conference on Robotic Computing (IRC)

作者： Yun-Hsuan Su Adnan Munawar Anton Deguet Andrew Lewis Kyle Lindgren Yangming Li Russell H. Taylor Gregory S. Fischer Blake Hannaford Peter Kazanzides Mount Holyoke College South Hadley MA USA Robotics Engineering Program Worcester Polytechnic Institute Worcester MA USA Johns Hopkins University Baltimore MD USA University of Washington Seattle WA USA Rochester NY USA

ISBN: (数字)9781728152370

ISBN: (纸本)9781728152387

Robot-assisted minimally invasive surgery has made a substantial impact in operating rooms over the past few decades with their high dexterity, small tool size, and impact on adoption of minimally invasive techniques. In recent years, intelligence and different levels of surgical robot autonomy have emerged thanks to the medical robotics endeavors at numerous academic institutions and leading surgical robot companies. To accelerate interaction within the research community and prevent repeated development, we propose the Collaborative robotics Toolkit (CRTK), a common API for the RAVEN-II and da Vinci Research Kit (dVRK) - two open surgical robot platforms installed at more than 40 institutions worldwide. CRTK has broadened to include other robots and devices, including simulated robotic systems and industrial robots. This common API is a community software infrastructure for research and education in cutting edge human-robot collaborative areas such as semi-autonomous teleoperation and medical robotics. This paper presents the concepts, design details and the integration of CRTK with physical robot systems and simulation platforms.

关键词： Medical robotics Minimally invasive surgery Service robots Conferences Collaboration Software Robots

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Development of a wall-climbing drone with a rotary arm for climbing various-shaped surfaces 15

Development of a wall-climbing drone with a rotary arm for c...

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15th International Conference on Ubiquitous Robots, UR 2018

作者： Myeong, Wancheol Song, Seungwon Myung, Hyun Dept. of Civil and Environmental Engineering Robotics Program KAIST Daejeon34141 Korea Republic of

ISBN: (纸本)9781538663349

In this paper, a novel wall-climbing drone installed with a rotary arm is proposed for climb operation on various shaped walls. Robots that can climb the wall are applicable to many operations such as structural health monitoring of high-rise buildings, bridges, nuclear power plants;maintenance of solar panels and glass walls;and visual inspection of the aircraft and vessels. Traditional wall-climbing robots use magnetic, vacuum, or bioinspired methods mimicking gecko foot for those purposes. However, those methods cannot be applied to various-shaped walls like inclined, and an obstacle existing walls such as window frames. To solve this problem, unmanned aerial vehicle (UAV)-type wall-climbing robots have recently been developed, but those types have disadvantages in terms of energy efficiency and impact in attaching and detaching processes. Therefore, in this paper, a wall-climbing drone with a rotary arm is proposed. The angle of the rotary arm is controlled depending on the slope angle of the wall to achieve energy efficiency. The drone was prototyped and tested in indoor environment to verify the feasibility of the mechanism. © 2018 IEEE.

关键词： Walls (structural partitions)

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Optomechanical dissipative solitons (vol 600, pg 75, 2021)

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NATURE 2022年第7896期602卷 E24-E24页

作者： Zhang, Jing Peng, Bo Kim, Seunghwi Monifi, Faraz Jiang, Xuefeng Li, Yihang Yu, Peng Liu, Lianqing Liu, Yu-xi Alu, Andrea Yang, Lan Department of Electrical and Systems Engineering Washington University St. Louis MO USA Department of Automation Tsinghua University Beijing P. R. China Photonics Initiative Advanced Science Research Center City University of New York New York NY USA Physics Program Graduate Center City University of New York New York NY USA State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang P. R. China Institute of Microelectronics Tsinghua University Beijing P. R. China

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Physical Fatigue Analysis of Assistive Robot Teleoperation via Whole-body Motion Mapping

Physical Fatigue Analysis of Assistive Robot Teleoperation v...

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2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Tsung-Chi Lin Achyuthan Unni Krishnan Zhi Li Robotics Engineering Program Worcester Polytechnic Institute Worcester MA USA Mechanical Engineering Department Worcester Polytechnic Institute Worcester MA USA

Robot teleoperation via motion mapping has been demonstrated to be an efficient and intuitive approach for controlling and teaching the whole-body motion coordination of humanoid robots. However, the physical fatigue in the usage of such robot teleoperation interfaces may prevent this approach to be widely used in large scale by diverse workforce populations. As a result, this paper conducts a user study to investigate the physical fatigue of teleoperators in the whole-body motion mapping teleoperation of a mobile humanoid assistive robot. Through a Vicon motion capture system, participants teleoperated the robot to perform general purpose assistive tasks that involve reaching-to-grasp, bimanual manipulation, loco-manipulation and human-robot interaction. We assess the physical fatigue based on surface electromyography (sEMG) measurement, and compare it between different tasks and muscles. Our analysis results indicate that: (1) Fatigue happens more in the tasks that involve more precise manipulation and steady posture maintenance; (2) Deltoids, Biceps and Trapezius are used more for such tasks and thus have more fatigue than others. These findings imply that automating the fatigue-causing task components may reduce the physical fatigue in motion mapping teleoperation.

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Simplified decision making in the belief space using belief sparsification

arXiv

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arXiv 2019年

作者： Elimelech, Khen Indelman, Vadim Robotics and Autonomous Systems Program Technion — Israel Institute of Technology Department of Aerospace Engineering Technion — Israel Institute of Technology

In this work, we introduce a new and efficient solution approach for the problem of decision making under uncertainty, which can be formulated as decision making in a belief space, over a possibly high-dimensional state space. Typically, to solve a decision problem, one should identify the optimal action from a set of candidates, according to some objective. We claim that one can often generate and solve an analogous yet simplified decision problem, which can be solved more efficiently. A wise simplification method can lead to the same action selection, or one for which the maximal loss in optimality can be guaranteed. Furthermore, such simplification is separated from the state inference and does not compromise its accuracy, as the selected action would finally be applied on the original state. First, we present the concept for general decision problems and provide a theoretical framework for a coherent formulation of the approach. We then practically apply these ideas to decision problems in the belief space, which can be simplified by considering a sparse approximation of their initial belief. The scalable belief sparsification algorithm we provide is able to yield solutions which are guaranteed to be consistent with the original problem. We demonstrate the benefits of the approach in the solution of a realistic active-SLAM problem and manage to significantly reduce computation time, with no loss in the quality of solution. This work is both fundamental and practical, and holds numerous possible extensions. Copyright © 2019, The Authors. All rights reserved.

关键词： Decision making

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Evaluation of a highly dexterous robotic manipulator for utilization of on-orbit servicing 70

Evaluation of a highly dexterous robotic manipulator for uti...

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70th International Astronautical Congress, IAC 2019

作者： King, Caitlin Griffin, Brand Low, Thomas Ortiz, Antonio Stephens, Matthew Troll, John Single-Person Spacecraft Genesis Engineering Solutions Inc. 4501 Boston Way LanhamMD20706 United States Robotics Program Taurus Robotic System SRI International 333 Ravenswood Avenue Menlo ParkCA94025 United States

The Single-Person Spacecraft (SPS) is being developed by Genesis engineering Solutions (GES) to provide the space industry with a new piloted, or remotely operated, EVA solution. The SPS provides a free-flyer inspection, repair, and servicing solution for host vehicles and stations, such as the lunar Gateway. This represents a new technology that will enhance human mobility and work efficiency during EVAs, as well as be operable through a locally commanded tele-operated mode. Hardware is being designed and built for a fully robotic demonstration mission, as a precursor to human operations, which will test and validate several key SPS systems in LEO. An effort is currently underway to develop an on-orbit dexterous manipulation capability. This will be achieved by combining the Taurus robotic system, developed by SRI International, with a custom positioning robotic platform that will operate in a seamless end-to-end control system. The commercially available Taurus robotic system is being validated as a highly skilled manipulator platform for spacecraft related tasks and is being evaluated for space-worthiness. A developmental task board has been built and will be used to perform activities such as MLI repair, hook and loop access, wire manipulation, optical performance, and harness connector removal/installation. The capabilities of the Taurus robotic system will be evaluated to complete the activities in a tele-operated mode particularly as compared to the capabilities of a spacesuit glove. The control program will also be evaluated for adapting to pre-routined scripts to perform the activities. Quantitative and qualitative results of the task board evaluations will be discussed and an assessment on how the results relate to the system requirements of the positioning robotic platform. In addition, significant robotic efforts of the program will be discussed including key trades related to the design and ground testing of the robotic system, a virtual environment zer

关键词： Repair

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Automotive start-stop engine based on fingerprint recognition system 1

Automotive start-stop engine based on fingerprint recognitio...

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1st International Conference on Automotive, Manufacturing, and Mechanical engineering, IC-AMME 2018

作者： Rivandi, Pranoko Winda, Astuti Satrio, Dewanto Solihin, Mahmud Iwan Automotive and Robotics Program Computer Engineering Department BINUS ASO School of Engineering Bina Nusantara University Jakarta11480 Indonesia Computer Engineering Department BINUS ASO School of Engineering Bina Nusantara University Jl. K. H. Syahdan No. 9 Kemanggisan Palmerah Jakarta11480 Indonesia Faculty of Engineering Technology and Built Environment UCSI University Cheras Kuala Lumpur56000 Malaysia

Automated vehicle security system plays an important rule in nowadays advance automotive technology. One of the methods which can be applied for a security system is based on biometric identification system. Fingerprint recognition is one of the biometric systems that can be applied to the security system. In this work, fingerprint recognition system to start the motorcycle engine is developed. The fingerprint of the owner and other authorized persons will be stored into the database, then while the time of starting the engine of the vehicle, the fingerprint will be validated with the database. The minutiae extraction method is applied to find the difference of fingerprint each other after turn the image into grayscale and thinning. After the extraction, the next step is finding the ridge edge and bifurcation. The result of the image will be used as input to the Artificial Neural Network (ANN) to recognize authorized person only. The experiment of fingerprint recognition system shows that automatic start-stop engine using fingerprint recognition system based minutiae extraction and Artificial Neural Network (ANN) has accuracy 100 % and 100 %, respectively. © 2019 The Authors, published by EDP Sciences.

关键词： Neural networks

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Measuring hand use in the home after cervical spinal cord injury using egocentric video

arXiv

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arXiv 2022年

作者： Bandini, Andrea Dousty, Mehdy Hitzig, Sander L. Craven, B. Catharine Kalsi-Ryan, Sukhvinder Zariffa, José KITE Research Institute Toronto Rehabilitation Institute University Health Network Canada The BioRobotics Institute Scuola Superiore Sant'Anna Pisa Italy Department of Excellence in Robotics and AI Scuola Superiore Sant'Anna Pisa Italy Institute of Biomedical Engineering University of Toronto TorontoON Canada Rehabilitation Sciences Institute Temerty Faculty of Medicine University of Toronto TorontoON Canada St. John's Rehab Research Program Sunnybrook Research Institute Sunnybrook Health Sciences Centre TorontoON Canada Department of Occupational Science & Occupational Therapy Temerty Faculty of Medicine University of Toronto TorontoON Canada Brain and Spinal Cord Rehabilitation Program Toronto Rehabilitation Institute University Health Network TorontoON Canada Division of Physical Medicine and Rehabilitation Department of Medicine Temerty Faculty of Medicine University of Toronto TorontoON Canada Department of Physical Therapy University of Toronto TorontoON Canada Edward S. Rogers Sr. Department of Electrical and Computer Engineering University of Toronto TorontoON Canada

Egocentric video has recently emerged as a potential solution for monitoring hand function in individuals living with tetraplegia in the community, especially for its ability to detect functional use in the home environment. The aim of this study was to develop and validate a wearable vision-based system for measuring hand use in the home among individuals living with tetraplegia. Several deep learning algorithms for detecting functional hand-object interactions were developed and compared. The most accurate algorithm was used to extract measures of hand function from 65 hours of unscripted video recorded at home by 20 participants with tetraplegia. These measures were: the percentage of interaction time over total recording time (Perc);the average duration of individual interactions (Dur);the number of interactions per hour (Num). To demonstrate the clinical validity of the technology, egocentric measures were correlated with validated clinical assessments of hand function and independence (Graded Redefined Assessment of Strength, Sensibility and Prehension - GRASSP, Upper Extremity Motor Score - UEMS, and Spinal Cord Independent Measure - SCIM). Hand-object interactions were automatically detected with a median F1-score of 0.80 (0.67-0.87). Our results demonstrated that higher UEMS and better prehension were related to greater time spent interacting, whereas higher SCIM and better hand sensation resulted in a higher number of interactions performed during the egocentric video recordings. For the first time, measures of hand function automatically estimated in an unconstrained environment in individuals with tetraplegia have been validated against internationally accepted measures of hand function. Future work will necessitate a formal evaluation of the reliability and responsiveness of the egocentric-based performance measures for hand use. © 2022, CC BY-NC-ND.

关键词： Video recording

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