Hierarchical Planning of Dynamic Movements without Scheduled Contact Sequences

Carlos Mastalli (1) , Ioannis Havoutis (2) , Michele Focchi (1) , Darwin G. Caldwell (1) , Claudio Semini (1)

1 IIT - Department of Advanced Robotics
2 Robot Learning & Interaction Group

Most animal and human locomotion behaviors for solving complex tasks involve dynamic motions and rich contact interaction. In fact, complex maneuvers need to consider dynamic movement and contact events at the same time. We present a hierarchical trajectory optimization approach for planning dynamic movements with unscheduled contact sequences. We compute whole-body motions that achieve goals that cannot be reached in a kinematic fashion. First, we find a feasible CoM motion according to the centroidal dynamics of the robot. Then, we refine the solution by applying the robot's full-dynamics model, where the feasible CoM trajectory is used as a warm-start point. To accomplish the unscheduled contact behavior, we use complementarity constraints to describe the contact model, i.e. environment geometry and non-sliding active contacts. Both optimization phases are posed as Mathematical Program with Complementarity Constraints (MPCC). Experimental trials demonstrate the performance of our planning approach in a set of challenging tasks.

Domaines: Robotique [cs.RO]; Optimisation et contrôle [math.OC]

Carlos Mastalli, Ioannis Havoutis, Michele Focchi, Darwin G. Caldwell, Claudio Semini. Hierarchical Planning of Dynamic Movements without Scheduled Contact Sequences. IEEE International Conference on Robotics and Automation (ICRA), May 2016, Stockholm, Sweden. ⟨hal-01661861⟩