Cloud based Real-time Multi-robot Collision Avoidance for Swarm Robotics

被引:14
|
作者
He, Hengjing [1 ]
Kamburugamuve, Supun [2 ]
Fox, Geoffrey C. [2 ]
Zhao, Wei [1 ]
机构
[1] Tsinghua Univ, Dept Elect Engn, State Key Lab Power Syst, Beijing, Peoples R China
[2] Indiana Univ, Sch Informat & Comp & CGL, Bloomington, IN 47405 USA
关键词
Internet of things; Cloud Computing; swarm robotics; swarm intelligence; collision avoidance; real-time stream processing;
D O I
10.14257/ijgdc.2016.9.6.30
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
Nowadays, Cloud Computing has brought many new and efficient approaches for computation-intensive application areas. One typical area is Cloud based real-time device control system, such as the IoT Cloud Platform. This kind of platform shifts computation load from devices to the Cloud and provides powerful processing capabilities to a simple device. In Swarm robotics, robots are supposed to be small, energy efficient and low-cost, but still smart enough to carry out individual and swarm intelligence. These two goals are normally contradictory to each other. Besides, in real world robot control, real-time on-line data processing is required, but most of the current Cloud Robotic Systems are focusing on off-line batch processing. However, Cloud based real-time device control system may provide a way that leads this research area out of its dilemma. This paper explores the availability of Cloud based real-time control of massive complex robots by implementing a relatively complicated but better performed local collision avoidance algorithm. The Cloud based application and corresponding Cloud driver, which connects the robot and the Cloud, are developed and deployed in Cloud environment. Simulation tests are carried out and the results show that, when the number of robots increases, by simply scaling computation resources for the application, the algorithm can still maintain the preset control frequency. Such characteristics verify that the Cloud Computing environment is a new platform for studying massive complex robots in swarm robotics.
引用
收藏
页码:339 / 357
页数:19
相关论文
共 50 条
  • [1] A Scalable Framework For Real-Time Multi-Robot, Multi-Human Collision Avoidance
    Bajcsy, Andrea
    Herbert, Sylvia L.
    Fridovich-Keil, David
    Fisac, Jaime F.
    Deglurkar, Sampada
    Dragan, Anca D.
    Tomlin, Claire J.
    [J]. 2019 INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA), 2019, : 936 - 943
  • [2] Cloud-based Framework for Scalable and Real-time Multi-robot SLAM
    Zhang, Pengfei
    Wang, Huaimin
    Ding, Bo
    Shang, Suning
    [J]. 2018 IEEE INTERNATIONAL CONFERENCE ON WEB SERVICES (IEEE ICWS 2018), 2018, : 147 - 154
  • [3] Collision Avoidance in Collaborative Robotics Based on Real-Time Skeleton Tracking
    Forlini, Matteo
    Neri, Federico
    Scoccia, Cecilia
    Carbonari, Luca
    Palmieri, Giacomo
    [J]. ADVANCES IN SERVICE AND INDUSTRIAL ROBOTICS, RAAD 2023, 2023, 135 : 81 - 88
  • [4] Behavior-based Multi-Robot Collision Avoidance
    Sun, Dali
    Kleiner, Alexander
    Nebel, Bernhard
    [J]. 2014 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA), 2014, : 1668 - 1673
  • [5] Collision avoidance in multi-robot systems
    Cai, Chengtao
    Yang, Chunsheng
    Zhu, Qidan
    Liang, Yanhua
    [J]. 2007 IEEE INTERNATIONAL CONFERENCE ON MECHATRONICS AND AUTOMATION, VOLS I-V, CONFERENCE PROCEEDINGS, 2007, : 2795 - 2800
  • [6] A REAL-TIME ROBOT ARM COLLISION AVOIDANCE SYSTEM
    SHAFFER, CA
    HERB, GM
    [J]. IEEE TRANSACTIONS ON ROBOTICS AND AUTOMATION, 1992, 8 (02): : 149 - 160
  • [7] Bluetooth RSSI Based Collision Avoidance in Multi-robot Environment
    Lijina, P.
    Kumaar, Nippun A. A.
    [J]. 2016 INTERNATIONAL CONFERENCE ON ADVANCES IN COMPUTING, COMMUNICATIONS AND INFORMATICS (ICACCI), 2016, : 2168 - 2174
  • [8] A Survey on Collision Avoidance for Multi-robot Systems
    Park, Jungwon
    Oh, Dahyun
    Kim, H. Jin
    [J]. Journal of Institute of Control, Robotics and Systems, 2024, 30 (04) : 402 - 411
  • [9] Real-Time Tactical Motion Planning and Obstacle Avoidance for Multi-Robot Cooperative Reconnaissance
    Boeing, Adrian
    Pangeni, Sushil
    Braeunl, Thomas
    Lee, Chang Su
    [J]. PROCEEDINGS 2012 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS (SMC), 2012, : 3117 - 3122
  • [10] Cloud-based real-time collaborative mapping and merging method for multi-robot with landmark information
    Zhuang, Wenmi
    Zhou, Fengyu
    Wan, Fang
    Yu, Bangguo
    [J]. PROCEEDINGS OF THE 32ND 2020 CHINESE CONTROL AND DECISION CONFERENCE (CCDC 2020), 2020, : 4319 - 4324