  The paper focuses on collision-inclusive motion planning for impact-resilient
mobile robots. We propose a new deformation recovery and replanning strategy to
handle collisions that may occur at run-time. Contrary to collision avoidance
methods that generate trajectories only in conservative local space or require
collision checking that has high computational cost, our method directly
generates (local) trajectories with imposing only waypoint constraints. If a
collision occurs, our method then estimates the post-impact state and computes
from there an intermediate waypoint to recover from the collision. To achieve
so, we develop two novel components: 1) a deformation recovery controller that
optimizes the robot's states during post-impact recovery phase, and 2) a
post-impact trajectory replanner that adjusts the next waypoint with the
information from the collision for the robot to pass through and generates a
polynomial-based minimum effort trajectory. The proposed strategy is evaluated
experimentally with an omni-directional impact-resilient wheeled robot. The
robot is designed in house, and it can perceive collisions with the aid of Hall
effect sensors embodied between the robot's main chassis and a surrounding
deflection ring-like structure.
