Robotic trajectory planning through collisional interaction
Mark Mote, Juan-Pablo Afman, Éric Féron · 2017
Collisions, if they are planned appropriately, can enable more effective navigation for robots capable of handling them. A mixed integer programming (MIP) formulation demonstrates the computational practicality of optimizing trajectories that comprise planned collisions. A novel framework is proposed to incorporate a physically realistic model of the hybrid contact dynamics as constraints in the optimization problem. Precise bounds are placed on the error from the simplifying assumptions, and it is shown that the error is driven to zero with finer temporal resolution. Implementation issues are considered in the context of regulation and damage upon contact. In particular, a damage quantification function is proposed. A simulated case study demonstrates that an increase in performance is achieved under this schema as compared to collision-free optimal trajectories.