Obstacle avoidance for a robotic manipulator with linear-quadratic Model Predictive Control

The problem of moving a six-degrees-of-freedom manipulator in an environment with unknown obstacles is considered. The manipulator is assumed to be equipped with an exteroceptive sensor that provides a partial sampling of the surroundings. A hierarchical control layout is proposed: in the outer layer, a path planner generates an obstacle-free trajectory based on the available local information; in the inner layer, an Inverse-Kinematics Model Predictive Controller tracks the trajectory while reactively avoiding unseen obstacles and self-collisions at a higher rate. By constructing a polytopic under-approximation of the free environment and employing a linearization of the task, the predictive controller features a convex quadratic cost and linear constraints, thus requiring the solution of a quadratic program at each time step. The proposed method is evaluated on the kinematic model of a MyCobot280 robotic arm, showing the potential for real-time feasibility.