Kinematically constrained workspace control via linear optimization

Z. Kingston, N. Dantam, and L. E. Kavraki, “Kinematically constrained workspace control via linear optimization,” in Proceedings of the IEEE-RAS 15th International Conference on Humanoid Robots (Humanoids), 2015, pp. 758–764.

Abstract

We present a method for Cartesian workspace control of a robot manipulator that enforces joint-level acceleration, velocity, and position constraints using linear optimization. This method is robust to kinematic singularities. On redundant manipulators, we avoid poor configurations near joint limits by including a maximum permissible velocity term to center each joint within its limits. Compared to the baseline Jacobian damped least-squares method of workspace control, this new approach honors kinematic limits, ensuring physically realizable control inputs and providing smoother motion of the robot. We demonstrate our method on simulated redundant and non-redundant manipulators and implement it on the physical 7-degree-of-freedom Baxter manipulator. We provide our control software under a permissive license.

Publisher: http://dx.doi.org/10.1109/HUMANOIDS.2015.7363455

PDF preprint: http://kavrakilab.org/publications/kingston2015lc3.pdf