用视觉与运动学耦合控制机械臂,提升实验室自动操作精度。
Multimodal Control of Manipulators: Coupling Kinematics and Vision for Self-Driving Laboratory Operations
- 基于雅可比矩阵的三种方法求解机械臂与夹爪联合运动
- 轨迹平滑性与关节速度/加速度/急动度指标显示DLS最优
- 适合自动化实验平台中复杂抓取任务的机械臂控制
运动规划方案用于在任务执行期间从初始位姿规划机械臂到目标位姿的运动。典型的运动规划方案包括轨迹规划方法和逆运动学求解器,分别用于确定运动轨迹和关节解。本文基于雅可比方法实现三种运动规划方案,用于驱动具有耦合手指夹爪的冗余机械臂沿指定轨迹运动。采用RRT*算法进行轨迹规划,利用螺旋理论建立的前向运动学方程求解机械臂与夹爪的关节解。逆解分别通过雅可比转置(JT)、伪逆(PI)和阻尼最小二乘(DLS)三种方法计算。基于螺旋理论公式获取机械臂与夹爪的局部雅可比矩阵及可操作性度量。分析生成轨迹的平滑性与均方根误差(RMSE),以及关节运动的速度连续性、加速度分布、急动度(jerk)和跃度(snap)等指标,以评估不同方法在特定任务中的效率。通过仿真研究对比分析了各方案的优劣,最终确定适用于特定任务的逆解技术。
原文摘要 · Abstract (English)
Motion planning schemes are used for planning motions of a manipulator from an initial pose to a final pose during a task execution. A motion planning scheme generally comprises of a trajectory planning method and an inverse kinematic solver to determine trajectories and joints solutions respectively. In this paper, 3 motion planning schemes developed based on Jacobian methods are implemented to traverse a redundant manipulator with a coupled finger gripper through given trajectories. RRT* algorithm is used for planning trajectories and screw theory based forward kinematic equations are solved for determining joint solutions of the manipulator and gripper. Inverse solutions are computed separately using 3 Jacobian based methods such as Jacobian Transpose (JT), Pseudo Inverse (PI), and Damped Least Square (DLS) methods. Space Jacobian and manipulability measurements of the manipulator and gripper are obtained using screw theory formulations. Smoothness and RMSE error of generated trajectories and velocity continuity, acceleration profile, jerk, and snap values of joint motions are analysed for determining an efficient motion planning method for a given task. Advantages and disadvantages of the proposed motion planning schemes mentioned above are analysed using simulation studies to determine a suitable inverse solution technique for the tasks.
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