针对家庭环境中服务机器人物品的抓取问题,提出一种改进的基于位置的视觉伺服抓取算法。首先,利用Naomark 标签完成对物体的快速识别,并通过世界平面单应矩阵分解对物体的位姿进行估计;然后,对 NAO 机器人的机械臂进行运动学建模,并分别设计单臂和双臂抓取的视觉伺服控制律;最后,为进一步提高抓取的稳定性和鲁棒性,对末端执行器进行路径规划。实验结果表明,本方法能够快速、稳定地抓取目标物品。
An improved position-based visual servo (PBVS) grasping algorithm was proposed for the service robot in home environment.First, the rapid identification of object was achieved by using Naomark, and the position and pose information of the object was estimated through the world homography matrix decomposition.Secondly, the kinematic model of the NAO robot′s arm was established, and PBVS control law was designed for either unimanual or bimanual grasping.Finally, for purpose of improving the stability and robustness of the grasping operation, path planning of the end-effector was added to the original PBVS control law.Experimental results showed that the proposed method could grasp the objects rapidly and stably.