LU Xiang, LIU Jingtai, LI Haifeng, LI Yan, SUN Lei. Attack and Defense Planning for Competitive Networked RobotsBased on Artificial Potential Field Method[J]. ROBOT, 2013, 35(2): 218-226. DOI: 10.3724/SP.J.1218.2013.00218
Citation: LU Xiang, LIU Jingtai, LI Haifeng, LI Yan, SUN Lei. Attack and Defense Planning for Competitive Networked RobotsBased on Artificial Potential Field Method[J]. ROBOT, 2013, 35(2): 218-226. DOI: 10.3724/SP.J.1218.2013.00218

Attack and Defense Planning for Competitive Networked RobotsBased on Artificial Potential Field Method

More Information
  • Received Date: June 10, 2012
  • Revised Date: November 27, 2012
  • Published Date: March 14, 2013
  • In order to beat the opponent in a competitive networked robot game, the robot need hit the target quickly and accurately while avoiding enemy's attack. In this paper, a novel approach combining trajectory planning and image-based visual servo control is proposed to quickly and effectively meet the requirements. Some main constraints such as attack avoiding, visibility, kinematic singularities, and joint velocity limits are taken into account. A trajectory is designed in the image space, which can be used in the image-based visual control directly. Simulations and experiments using an eye-in-hand robotic system on a 6-DOF (degree of freedom) robot manipulator are carried out to confirm that our approach can help the robot to hit the target and avoid attacks.
  • [1]
    刘景泰,李海丰,孙雷,等.Tele-LightSaber——一种高对抗度竞争型网络机器人系统[J].机器人,2009,31(6):505-512. Liu J T, Li H F, Sun L, et al. Tele-LightSaber - A kind of competitive networked robots with high degree of opposition[J]. Robot, 2009, 31(6): 505-512.
    [2]
    Thuilot B, Martinet P, Cordesses L, et al. Position based visual servoing: Keeping the object in the field of vision[C]//IEEE International Conference on Robotics and Automation. Piscataway, NJ, USA: IEEE, 2002: 1624-1629.
    [3]
    Chesi G, Hashimoto K, Prattichizzo D, et al. Keeping features in the field of view in eye-in-hand visual servoing: A switching approach[J]. IEEE Transactions on Robotics, 2004, 20(5): 908-913.  
    [4]
    Mansard N, Chaumette F. A new redundancy formalism for avoidance in visual servoing[C]//IEEE/RSJ International Conference on Intelligent Robots and Systems. Piscataway, NJ, USA: IEEE, 2005: 1694-1700.
    [5]
    Hashimoto K, Noritsugu T. Potential switching control in visual servo[C]//IEEE International Conference on Robotics and Automation. Piscataway, NJ, USA: IEEE, 2000: 2765-2770.
    [6]
    Léonard S, Croft E A, Little J J. Dynamic visibility checking for vision-based motion planning[C]//IEEE International Conference on Robotics and Automation. Piscataway, NJ, USA: IEEE, 2008: 2283-2288.
    [7]
    Michel P, Scheurer C, Kuffner J, et al. Planning for robust execution of humanoid motions using future perceptive capability[C]//IEEE/RSJ International Conference on Intelligent Robots and Systems. Piscataway, NJ, USA: IEEE, 2007: 3223-3228.
    [8]
    Chesi G, Hung Y.S. Global path-planning for constrained and optimal visual servoing[J]. IEEE Transactions on Robotics, 2007, 23(5): 1050-1060.  
    [9]
    Allotta B, Fioravanti D. 3D motion planning for image-based visual servoing tasks[C]//IEEE International Conference on Robotics and Automation. Piscataway, NJ, USA: IEEE, 2005: 2173-2178.
    [10]
    Kazemi M, Gupta K, Mehrandezh M. Global path planning for robust visual servoing in complex environments[C]//IEEE International Conference on Robotics and Automation. Piscataway, NJ, USA: IEEE, 2009: 326-332.
    [11]
    Kazemi M, Mehrandezh M, Gupta K. Kinodynamic planning for visual servoing[C]//IEEE International Conference on Robotics and Automation. Piscataway, NJ, USA: IEEE, 2011: 2478-2484.
    [12]
    Mezouar Y, Chaumette F. Path planning in image space for robust visual servoing[C]//IEEE International Conference on Robotics and Automation. Piscataway, NJ, USA: IEEE, 2000: 2759-2764.
    [13]
    Mezouar Y, Chaumette F. Path planning for robust image-based control[J]. IEEE Transactions on Robotics and Automation, 2002, 18(4): 534-549.  
    [14]
    Deng L F, Janabi-Sharifi F, Wilson W J. Hybrid motion control and planning strategies for visual servoing[J]. IEEE Transactions on Industrial Electronics, 2005, 52(4): 1024-1040.  
    [15]
    卢翔,刘景泰,于凯妍,等.面向竞争型网络机器人的运动目标快速检测[J].机器人,2011,33(6):658-665,672. Lu X, Liu J T, Yu K Y, et al. Rapid detection of moving target in the competitive networked robots[J]. Robot, 2011, 33(6): 658-665,672.
    [16]
    于凯妍,刘景泰,卢翔,等.竞争型机器人仿真系统设计与实现[J].机器人,2011,33(6):649-657. Yu K Y, Liu J T, Lu X, et al. Design and implementation of simulation system for the competitive robot system[J]. Robot, 2011, 33(6): 649-657.
    [17]
    Tsuji T, Tanaka Y, Morasso P G, et al. Bio-mimetic trajectory generation of robots via artificial potential field with time base generator[J]. IEEE Transactions on Systems, Man, and Cybernetics: Part C, 2002, 32(4): 426-439.  
    [18]
    Jing R, McIsaac K A, Patel R V, et al. A potential field model using generalized sigmoid functions[J]. IEEE Transactions on Systems, Man, and Cybernetics: Part B, 2007, 37(2): 477-484.  
    [19]
    Agirrebeitia J, Avilés R, De Bustos I F, et al. A new APF strategy for path planning in environments with obstacles[J]. Mechanism and Machine Theory, 2005, 40(6): 645-658.  
    [20]
    Vaezi M, Samavati F C, Jazeh H E S, et al. Singularity analysis of 6DOF Stäubli\copyright TX40 robot[C]//IEEE International Conference on Mechatronics and Automation. Piscataway, NJ, USA: IEEE, 2011: 446-451.
    [21]
    Chaumette F, Hutchinson S. Visual servo control. Part I:Basic approaches[J]. IEEE Robotics & Automation Magazine, 2006, 13(4): 82-90.  
    [22]
    Li H F, Liu J T, Li Y, et al. Visual servoing with an uncalibrated eye-in-hand camera[C]//Chinese Control Conference. Piscataway, NJ, USA: IEEE, 2010: 3666-3672.

Catalog

    Article views (16) PDF downloads (733) Cited by()
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return