卢翔, 刘景泰, 李海丰, 李岩, 孙雷. 基于人工势场法的竞争型网络机器人攻防规划[J]. 机器人, 2013, 35(2): 218-226. DOI: 10.3724/SP.J.1218.2013.00218
引用本文: 卢翔, 刘景泰, 李海丰, 李岩, 孙雷. 基于人工势场法的竞争型网络机器人攻防规划[J]. 机器人, 2013, 35(2): 218-226. DOI: 10.3724/SP.J.1218.2013.00218
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

基于人工势场法的竞争型网络机器人攻防规划

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

  • 摘要: 在竞争型网络机器人攻防过程中,为了能够战胜对手,需要快速准确打击目标同时躲避敌方的攻击.本文结合轨迹规划及基于图像的视觉伺服控制提出了一种快速有效的解决方法. 同时考虑了一些主要约束,如躲避敌方打击、可视性、运动学奇异区及关节速度限制等.该方法在图像空间规划一条轨迹,得到的轨迹可以直接用来进行基于图像的视觉伺服控制. 最后利用基于6自由度机械臂的机器人手眼系统进行仿真和实验,证明本文提出的方法能够在己方有效打击目标的同时躲避对方的攻击.

     

    Abstract: 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.

     

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