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Lessons learned:Symbiotic autonomous robot ecosystem for nuclear environments

IET Cyber-Systems and robotics 2023年第4期5卷 63-86页

作者： Daniel Mitchell Paul Dominick Emor Baniqued Abdul Zahid Andrew West Bahman Nouri Rahmat Abadi Barry Lennox Bin Liu Burak Kizilkaya David Flynn David John Francis Erwin Jose Lopez Pulgarin Guodong Zhao Hasan Kivrak Jamie Rowland Douglas Blanche Jennifer David Jingyan Wang Joseph Bolarinwa Kanzhong Yao Keir Groves Liyuan Qi Mahmoud A.Shawky Manuel Giuliani Melissa Sandison Olaoluwa Popoola Ognjen Marjanovic Paul Bremner Samuel Thomas Harper Shivoh Nandakumar Simon Watson Subham Agrawal Theodore Lim Thomas Johnson Wasim Ahmad Xiangmin Xu Zhen Meng Zhengyi Jiang James Watt School of Engineering Autonomous Systems and Connectivity DivisionUniversity of GlasgowGlasgowUK Department of Electrical and Electronic Engineering The University of ManchesterManchesterUK Bristol robotics Laboratory University of the West of EnglandBristolUK Heriot-Watt University EdinburghUK

Nuclear facilities have a regulatory requirement to measure radiation levels within Post Operational Clean Out(POCO)around nuclear facilities each year,resulting in a trend towards robotic deployments to gain an improved understanding during nuclear decommissioning phases.The UK Nuclear Decommissioning Authority supports the view that human-in-the-loop(HITL)robotic deployments are a solution to improve procedures and reduce risks within radiation characterisation of nuclear sites.The authors present a novel implementation of a Cyber-Physical System(CPS)deployed in an analogue nuclear environment,comprised of a multi-robot(MR)team coordinated by a HITL operator through a digital twin interface.The development of the CPS created efficient partnerships across systems including robots,digital systems and human.This was presented as a multi-staged mission within an inspection scenario for the hetero-geneous Symbiotic Multi-robot Fleet(SMuRF).Symbiotic interactions were achieved across the SMuRF where robots utilised automated collaborative governance to work together,where a single robot would face challenges in full characterisation of radiation.Key contributions include the demonstration of symbiotic autonomy and query-based learning of an autonomous mission supporting scalable autonomy and autonomy as a service.The coordination of the CPS was a success and displayed further challenges and improvements related to future MR fleets.

关键词： cyber-systems field robotics hazardous inspection human robot interaction industrial robotics mobile robots multi-agent systems multi-robot systems robotics service robots

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Uncanny valley for interactive social agents:an experimental study

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Virtual Reality & Intelligent Hardware 2022年第5期4卷 393-405页

作者： Nidhi MISHRA Manoj RAMANATHAN Gauri TULSULKAR Nadia Magneat THALMANN Institute for Media Innovation Nanyang Technological University637553Singapore Rehabilitation Research Institute of Singapore Nanyang Technological University308232Singapore MIRALab BattelleBuilding A 7Route de DrizeCH-1227 CarougeGenevaSwitzerland

Background The uncanny valley hypothesis states that users may experience discomfort when inter-acting with almost human-like artificial characters.Advancements in artificial intelligence,robotics,and computer graphics have led to the development of life-like virtual humans and humanoid robots.Revisiting this hypothesis is necessary to check whether they positively or negatively affect the current population,who are highly accustomed to the latest technologies.Methods In this study,we present a unique evaluation of the uncanny valley hypothesis by allowing participants to interact live with four humanoid robots that have varying levels of human-likeness.Each participant completed a survey questionnaire to evaluate the affinity of each robot.Additionally,we used deep learning methods to quantify the participants’emotional states using multimodal cues,including visual,audio,and text cues,by recording the participant-robot interactions.Results Multi-modal analysis and surveys provided interesting results and insights into the uncanny valley hypothesis.

关键词： Uncanny valley hypothesis human robot interaction Interactive robots humanoid robots Virtual humans

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Development of an Anthropomorphic robotic Arm and Hand for Interactive humanoids

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Journal of Bionic Engineering 2012年第2期9卷 133-142页

作者： Jamie K. Paik Bu Hyun Shin Young-bong Bang Young-Bo Shim The Institute of Mechanical Engineering EPFL STI I G M UPPAIK BM 4118 （Bdtiment BM） Station 17 Switzerland Department of Mechanical Engineering Hanbat University Daejeon 305-719 South Korea Advanced Institutes of Convergence Technology Seoul National University Suwon-si Gyeonggi-do 443-270 South Korea Mechatronics and Manufacturing Technology Center Samsung Electronics Co Suwon-si Gyeonggi-do 443-742 South Korea

humanoid robots are designed and built to mimic human form and movement. Ultimately, they are meant to resemble the size and physical abilities of a human in order to function in human-oriented environments and to work autonomously but to pose no physical threat to humans. Here, a humanoid robot that resembles a human in appearance and movement is built using powerful actuators paired with gear trains, joint mechanisms, and motor drivers that are all encased in a package no larger than that of the human physique. In this paper, we propose the construction of a humanoid-applicable anthropomorphic 7-DoF arm complete with an 8-DoF hand. The novel mechanical design of this humanoid ann makes it sufficiently compact to be compatible with currently available narrating-model humanoids, and to be sufficiently powerful and flexible to be functional; the number of degrees of freedom endowed in this robotic arm is sufficient for executing a wide range of tasks, including dexterous hand movements. The developed humanoid arm and hand are capable of sensing and interpreting incoming external force using the motor in each joint current without conventional torque sensors. The humanoid ann adopts an algorithm to avoid obstacles and the dexterous hand is capable of grasping objects. The developed robotic ann is suitable for use in an interactive humanoid robot.

关键词： humanoid arm humanoid hand human robot interaction safe robot arm and torque sensing

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Type Design and Behavior Control for Six Legged robots

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Chinese Journal of Mechanical Engineering 2018年第3期31卷 11-22页

作者： Ling Fang Feng Gao State Key Laboratory of Mechanical System and Vibration Shanghai Jiao Tong University

The research on legged robots attracted much attention both from the academia and industry. Legged robots are multi-input multi-output with multiple end-e ector systems. Therefore,the mechanical design and control framework are challenging issues. This paper reviews the development of type synthesis and behavior control on legged robots; introduces the hexapod robots developed in our research group based on the proposed type synthesis method. The control framework for legged robots includes data driven layer,robot behavior layer and robot execution layer. Each layer consists several components which are explained in details. Finally,various experiments were conducted on several hexapod robots. The summarization of the type synthesis and behavior control design constructed in this paper would provide a unified platform for communications and references for future advancement for legged robots.

关键词： Legged robot Type synthesis human robot interaction Control framework

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Deep reinforcement learning for shared control of mobile robots

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IET Cyber-Systems and robotics 2021年第4期3卷 315-330页

作者： Chong Tian Shahil Shaik Yue Wang Mechanical Engineering Department Clemson UniversityClemsonSouth CarolinaUSA

Shared control of mobile robots integrates manual input with auxiliary autonomous controllers to improve the overall system performance.However,prior work that seeks to find the optimal shared control ratio needs an accurate human model,which is usually challenging to obtain.In this study,the authors develop an extended Twin Delayed Deep Deterministic Policy Gradient(DDPG)(TD3X)-based shared control framework that learns to assist a human operator in teleoperating mobile robots optimally.The robot's states,shared control ratio in the previous time step,and human's control input is used as inputs to the reinforcement learning(RL)agent,which then outputs the optimal shared control ratio between human input and autonomous controllers without knowing the human model.Noisy softmax policies are developed to make the TD3X algorithm feasible under the constraint of a shared control ratio.Furthermore,to accelerate the training process and protect the robot,a navigation demonstration policy and a safety guard are developed.A neural network(NN)structure is developed to maintain the correlation of sensor readings among heterogeneous input data and improve the learning speed.In addition,an extended DAGGER(DAGGERX)human agent is developed for training the RL agent to reduce human workload.robot simulations and experiments with humans in the loop are conducted.The results show that the DAGGERX human agent can simulate real human inputs in the worst-case scenarios with a mean square error of 0.0039.Compared to the original TD3 agent,the TD3X-based shared control system decreased the average collision number from 387.3 to 44.4 in a simplistic environment and 394.2 to 171.2 in a more complex environment.The maximum average return increased from 1043 to 1187 with a faster converge speed in the simplistic environment,while the performance is equally good in the complex environment because of the use of an advanced human agent.In the human subject tests,participants'average perceived workload was significantly lower in shared control

关键词： control deep learning human robot interaction mobile robots reinforcement learning

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