Tracking Cartesian motion with end~effectors is a fundamental task in robot control. For motion that is not known in advance, the solvers must find fast solutions to the inverse kinematics (IK) problem for discretely sampled target poses. On joint control level, however, the robot's actuators operate in a continuous domain, requiring smooth transitions between individual states. In this work, we present a boost to the well-known Jacobian transpose method to address this goal, using the mass matrix of a virtually conditioned twin of the manipulator. Results on the UR10 show superior convergence and quality of our dynamics-based solver against the plain Jacobian method. Our algorithm is straightforward to implement as a controller, using common robotics libraries.

翻译：追踪末端执行器的笛卡尔运动是机器人控制中的基本任务。对于预先未知的运动，求解器必须针对离散采样的目标位姿快速求解逆运动学问题。然而，在关节控制层面，机器人的执行器在连续域中运行，需要各状态之间的平滑过渡。在本工作中，我们针对雅可比转置法这一经典方法进行了改进，利用虚拟条件处理后的机械臂质量矩阵来提升性能。在UR10上的实验结果表明，相较于标准雅可比方法，我们所提出的动力学求解器在收敛速度和解算质量上均具有显著优势。该算法可通过常见机器人库直接实现为控制器。