Tension-Aware Motion Planning for Tethered Robots

被引:0
|
作者
Lima, Rogerio R. [1 ]
Pereira, Guilherme A. S. [1 ]
机构
[1] West Virginia Univ, Benjamin M Statler Coll Engn & Mineral Resources, Dept Mech Mat & Aerosp Engn, Morgantown, WV 26506 USA
关键词
tethered robots; path planning; minimum tension; FRICTION;
D O I
10.3390/robotics14020011
中图分类号
TP24 [机器人技术];
学科分类号
080202 ; 1405 ;
摘要
This paper presents a path-planning approach for tethered robots. The proposed planner finds paths that minimize the tether tension due to tether-obstacle and tether-floor interaction. The method assumes that the tether is managed externally by a tether management system and pulled by the robot. The planner is initially formulated for ground robots in a 2D environment and then extended for 3D scenarios, where it can be applied to tethered aerial and underwater vehicles. The proposed approach assumes a taut tether between two consecutive contact points and knowledge of the coefficient of friction of the obstacles present in the environment. The method first computes the visibility graph of the environment, in which each node represents a vertex of an obstacle. Then, a second graph, named the tension-aware graph, is built so that the tether-environment interaction, formulated in terms of tension, is computed and used as the cost of the edges. A graph search algorithm (e.g., Dijkstra) is then used to compute a path with minimum tension, which can help the tethered robot reach longer distances by minimizing the tension required to drag the tether along the way. This paper presents simulations and a real-world experiment that illustrate the characteristics of the method.
引用
收藏
页数:19
相关论文
共 50 条
  • [31] The Research of Motion Planning for Humanoid Robots
    Lu Xueqin
    Qiu Rongfu
    2009 INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE AND COMPUTATIONAL INTELLIGENCE, VOL II, PROCEEDINGS, 2009, : 322 - 326
  • [32] A Motion Planning System for Mobile Robots
    Tuncer, Adem
    Yildirim, Mehmet
    Erkan, Kadir
    ADVANCES IN ELECTRICAL AND COMPUTER ENGINEERING, 2012, 12 (01) : 57 - 62
  • [33] Collaborative motion planning of autonomous robots
    Okada, Takashi
    Beuran, Razvan
    Nakata, Junya
    Tan, Yasuo
    Shinoda, Yoichi
    2007 INTERNATIONAL CONFERENCE ON COLLABORATIVE COMPUTING: NETWORKING, APPLICATIONS AND WORKSHARING, 2008, : 328 - 335
  • [34] Adaptive Motion Planning for Humanoid Robots
    Vahrenkamp, Nikolaus
    Scheurer, Christian
    Asfour, Tamim
    Kuffner, James
    Dillmann, Ruediger
    2008 IEEE/RSJ INTERNATIONAL CONFERENCE ON ROBOTS AND INTELLIGENT SYSTEMS, VOLS 1-3, CONFERENCE PROCEEDINGS, 2008, : 2127 - +
  • [35] Distributed motion planning for modular robots
    Gregersen, K
    Petersen, HG
    Petersen, ML
    SENSOR FUSION AND DECENTRALIZED CONTROL IN ROBOTIC SYSTEMS IV, 2001, 4571 : 150 - 161
  • [36] Motion-planning for welding robots
    Verbarg, K
    IECON '98 - PROCEEDINGS OF THE 24TH ANNUAL CONFERENCE OF THE IEEE INDUSTRIAL ELECTRONICS SOCIETY, VOLS 1-4, 1998, : 2227 - 2232
  • [37] Constrained Motion Planning for Industrial Robots
    Antonelli, Gianluca
    Chiaverini, Stefano
    Curatella, Cataldo
    Marino, Alessandro
    2009 IEEE INTERNATIONAL CONFERENCE ON AUTOMATION AND LOGISTICS ( ICAL 2009), VOLS 1-3, 2009, : 1933 - +
  • [38] Optimal Motion Planning for Humanoid Robots
    El Khoury, Antonio
    Lamiraux, Florent
    Taix, Michel
    2013 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA), 2013, : 3136 - 3141
  • [39] Nonholonomic Motion Planning of Mobile Robots
    Galicki, Miroslaw
    ROBOT MOTION AND CONTROL 2009, 2009, 396 : 277 - 286
  • [40] Motion Trajectory Planning of Biped Robots
    Zhang, Chenxi
    Li, Junjian
    Xue, Bingxin
    PROCEEDINGS OF 2019 IEEE 3RD INFORMATION TECHNOLOGY, NETWORKING, ELECTRONIC AND AUTOMATION CONTROL CONFERENCE (ITNEC 2019), 2019, : 727 - 730