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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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Opportunistic Synthesis in Reactive Games under Information Asymmetry

Opportunistic Synthesis in Reactive Games under Information ...

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Annual Allerton Conference on Communication, Control, and Computing

作者： Jie Fu Department of Electrical and Computer Engineering Robotics Engineering Program Worcester Polytechnic Institute Worcester MA USA

Reactive synthesis [1]is used to synthesize a provably-correct strategy (controller) with respect to a given Linear Temporal Logic (LTL) specification in a dynamic, potentially adversarial environment. The core idea of reactive synthesis is to model the interaction between a controlled agent (called the robot) and its dynamic and uncontrollable environment as a two-player turn-based zero-sum game. In particular, players' Boolean payoffs are specified by temporal logic formulas [2]-a rich language that can expressive properties such as safety, liveness, stability, and temporally extended goals.

关键词： Games Robots Task analysis Game theory Vehicle dynamics Computer security

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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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Region-based planning for 3D within-hand-manipulation via variable friction robot fingers and extrinsic contacts

arXiv

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arXiv 2020年

作者： Sahin, Alp Spiers, Adam J. Calli, Berk Robotics Engineering Program Worcester Polytechnic Institute 85 Prescott Street WorcesterMA01605 United States The Electrical and Electronic Engineering Department Imperial College London LondonSW7 2AZ United Kingdom

Attempts to achieve robotic Within-Hand-Manipulation (WIHM) generally utilize either high-DOF robotic hands with elaborate sensing apparatus or multiarm robotic systems. In prior work we presented a simple robot hand with variable friction robot fingers, which allow a low-complexity approach to within-hand object translation and rotation, though this manipulation was limited to planar actions. In this work we extend the capabilities of this system to 3D manipulation with a novel region-based WIHM planning algorithm and utilizing extrinsic contacts. The ability to modulate finger friction enhances extrinsic dexterity for three-dimensional WIHM, and allows us to operate in the quasi-static level. The region-based planner automatically generates 3D manipulation sequences with a modified A* formulation that navigates the contact regions between the fingers and the object surface to reach desired regions. Central to this method is a set of object-motion primitives (i.e. within-hand sliding, rotation and pivoting), which can easily be achieved via changing contact friction. A wide range of goal regions can be achieved via this approach, which is demonstrated via real robot experiments following a standardized in-hand manipulation benchmarking protocol. © 2020, CC BY-NC-SA.

关键词： Robotic arms

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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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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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A Novel Approach to Differentiate COVID-19 Pneumonia in Chest X-ray

A Novel Approach to Differentiate COVID-19 Pneumonia in Ches...

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IEEE Symposium on Bioinformatics and Bioengineering (BIBE)

作者： Luis Vinícius de Moura Caroline Machado Dartora Christian Mattjie de Oliveira Rodrigo Coelho Barros Ana Maria Marques da Silva School of Technology Medical Imaging Computing Laboratory-MEDICOM PUCRS Porto Alegre Brazil School of Medicine Graduate Program in Biomedical Gerontology PUCRS Porto Alegre Brazil School of Technology Machine Intelligence and Robotics Research Group PUCRS Porto Alegre Brazil

ISBN: (数字)9781728195742

ISBN: (纸本)9781728195759

Radiological chest examinations like chest X-ray play a fundamental role in the fight against the outbreak of COVID-19 pneumonia, caused by the coronavirus strain SARSCov-2. This study aims to investigate classification models to differentiate chest X-ray images of COVID-19-based and typical pneumonia using hand-crafted radiomic features, understanding the distinctive radiographic features of COVID19. A total of 136 segmented chest X-rays from two public databases were used to train and evaluate the classification methods. The PyRadiomics library was used to extract first and second-order statistical texture features in the right (R), left (L), and in superior, middle and bottom lung zones for each lung side. For performing feature selection, data was split in training (80%) and test (20%) sets. Stratified K-folds (K=5) was used within the training dataset for cross-validation. The most relevant radiomic features were selected after measuring validation accuracy and relative feature importance. Support vector machines (SVM), random forest (RF), AdaBoost (AB), and logistic regression (LR) were analyzed as potential classifiers. The AB model was the best discriminant method between features related to COVID-19-based when compared to typical pneumonia, using a model of lung segmentation in six distinct lung zones (AUC =0.98). Our study shows a predominance of radiomic feature selection in the right lung, with a tendency to the upper lung zone.

关键词： COVID-19 Training Support vector machines Lung Feature extraction X-ray imaging Radiomics

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Topological Approximate Dynamic programming under Temporal Logic Constraints

arXiv

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arXiv 2019年

作者： Li, Lening Fu, Jie Robotics Engineering Program Department of Electrical and Computer Engineering Worcester Polytechnic Institute WorcesterMA01609 United States

In this paper, we develop a model-free approximate dynamic programming method for stochastic systems modeled as Markov decision processes to maximize the probability of satisfying high-level system specifications expressed in a subclass of temporal logic formulas—syntactically co-safe linear temporal logic. Our proposed method includes two steps: First, we decompose the planning problem into a sequence of sub-problems based on the topological property of the task automaton which is translated from a temporal logic formula. Second, we extend a model-free approximate dynamic programming method to solve value functions, one for each state in the task automaton, in an order reverse to the causal dependency. Particularly, we show that the run-time of the proposed algorithm does not grow exponentially with the size of specifications. The correctness and efficiency of the algorithm are demonstrated using a robotic motion planning example. Copyright © 2019, The Authors. All rights reserved.

关键词： Specifications

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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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