Hernandez-Barragan Jesus, Villaseñor Carlos, Lopez-Franco Carlos, Arana-Daniel Nancy, Gomez-Avila Javier
University Center for Exact Sciences and Engineering, Universidad de Guadalajara, Guadalajara, Jalisco, Mexico.
PeerJ Comput Sci. 2024 Nov 29;10:e2559. doi: 10.7717/peerj-cs.2559. eCollection 2024.
This article presents an implementation of visual servoing (VS) for a redundant mobile manipulator in an eye-in-hand configuration. We used the image based visual servoing (IBVS) scheme, which means the pose control of the robot is based on the error features in the image of a camera. Conventional eye-in-hand VS requires the inversion of a Jacobian matrix, which can become rank deficient, provoking kinematic singularities. In this work, the inversion of the Jacobian matrix is solved using damped least squares (DLS) to reduce singularities and smooth out discontinuities. In addition, a task prioritization scheme is proposed where a primary task performs the eye-in-hand IBVS task, and a secondary task maximizes a manipulability measure to avoid singularities. Finally, a gravity compensation term is also considered and defined on the basis of the image space error. The effectiveness of the proposed algorithm is demonstrated through both simulation and experimental results considering the Kuka YouBot.
本文提出了一种针对眼在手配置的冗余移动机械手的视觉伺服（VS）实现方法。我们采用了基于图像的视觉伺服（IBVS）方案，这意味着机器人的位姿控制基于相机图像中的误差特征。传统的眼在手视觉伺服需要求雅可比矩阵的逆，而该矩阵可能会出现秩亏缺，引发运动学奇异性。在这项工作中，使用阻尼最小二乘法（DLS）求解雅可比矩阵的逆，以减少奇异性并消除不连续性。此外，还提出了一种任务优先级方案，其中主要任务执行眼在手IBVS任务，次要任务最大化可操作性度量以避免奇异性。最后，还基于图像空间误差考虑并定义了重力补偿项。通过考虑库卡尤伯特机器人的仿真和实验结果，证明了所提算法的有效性。
