Rearranging the Environment to Maximize Energy with a Robotic Circuit Drawing
2022
会议录名称2022 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND BIOMIMETICS, ROBIO 2022
页码2281-2286
发表状态已发表
DOI10.1109/ROBIO55434.2022.10011990
摘要The ability of acquiring energy form environments is greatly beneficial for robot to function in uncertain environments. In this work, we present a robot capable of drawing circuits with conductive ink while also rearranging the visual world to receive maximum energy from a power source. A range of circuit drawing tasks is designed to simulate real-world scenarios, including avoiding physical obstacles and regions that would discontinue drawn circuits. We adopt the state-of-the-art Transporter networks for pick-and-place manipulation from visual observation. We conduct experiments in both simulation and real-world settings, and our results show that, with a small number of demonstrations, the robot learns to rearrange the placement of objects (removing obstacles and bridging areas unsuitable for drawing) and to connect a power source with a minimum amount of conductive ink. As autonomous robots become more and more involved in our daily lives, our proposed approach brings a novel way for machines to keep themselves functional by rearranging their surroundings to create their own electric circuits. © 2022 IEEE.
关键词Robots Conductive ink Energy Energy forms Pick and place Power sources Real-world scenario State of the art Uncertain environments Visual observations Visual world
会议名称2022 IEEE International Conference on Robotics and Biomimetics, ROBIO 2022
会议地点No.1, Yuntou Road, Gasa Town, Jinghong, China
会议日期December 5, 2022 - December 9, 2022
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收录类别EI
语种英语
出版者Institute of Electrical and Electronics Engineers Inc.
EI入藏号20230613554875
EI主题词Timing circuits
EI分类号713.4 Pulse Circuits ; 731.5 Robotics
原始文献类型Conference article (CA)
来源库IEEE
文献类型会议论文
条目标识符https://kms.shanghaitech.edu.cn/handle/2MSLDSTB/282054
专题信息科学与技术学院
信息科学与技术学院_PI研究组_Sören Schwertfeger组
信息科学与技术学院_硕士生
作者单位
1.Hamlyn Centre, Imperial College, London, UK
2.Department of Computer Science, University of York, UK
3.School of Information Science and Technology, ShanghaiTech University, China
4.Robotics Engineering, Worcester Polytechnic Institute, USA
推荐引用方式
GB/T 7714
Xianglong Tan,Zhikang Liu,Chen Yu,et al. Rearranging the Environment to Maximize Energy with a Robotic Circuit Drawing[C]:Institute of Electrical and Electronics Engineers Inc.,2022:2281-2286.
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