Inverse Kinematics with Forward Dynamics Solvers for Sampled Motion Tracking
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Tracking Cartesian trajectories with end-effectors is a fundamental task in robot control. For motion that is not known a priori, 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 present robotics libraries.
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