HyRRT-Connect: Bidirectional Motion Planning for Hybrid Dynamical Systems
This addresses motion planning for hybrid systems, which is important for robotics and control applications, but it appears incremental as it builds on existing RRT methods.
The paper tackles motion planning for hybrid dynamical systems by proposing HyRRT-Connect, a bidirectional RRT algorithm that propagates forward and backward in hybrid time to find and connect partial plans, and it demonstrates computational improvement in examples like an actuated bouncing ball and a walking robot.
This paper proposes a bidirectional rapidly-exploring random trees (RRT) algorithm to solve the motion planning problem for hybrid systems. The proposed algorithm, called HyRRT-Connect, propagates in both forward and backward directions in hybrid time until an overlap between the forward and backward propagation results is detected. Then, HyRRT-Connect constructs a motion plan through the reversal and concatenation of functions defined on hybrid time domains, ensuring that the motion plan satisfies the given hybrid dynamics. To address the potential discontinuity along the flow caused by tolerating some distance between the forward and backward partial motion plans, we reconstruct the backward partial motion plan by a forward-in-hybrid-time simulation from the final state of the forward partial motion plan. effectively eliminating the discontinuity. The proposed algorithm is applied to an actuated bouncing ball system and a walking robot example to highlight its computational improvement.