Dynamic Movement Primitives: Volumetric Obstacle Avoidance Using Dynamic Potential Functions

Abstract Obstacle avoidance for Dynamic Movement Primitives (DMPs) is still a challenging problem. In our previous work, we proposed framework obstacle based on superquadric potential functions to represent volumes. this extend work include the velocity of system in definition potential. Our formulations guarantee smoother behavior with respect state-of-the-art point-like methods. Moreover, new formulation allows obtaining proximity than when using static (i.e. independent) We validate simulated multi-robot scenario and different real robots: pick-and-place task an industrial manipulator surgical robot show scalability; navigation mobile dynamic environment.