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This paper presents a multi-contact approach to generalized humanoid fallmitigation planning that unifies inertial shaping, protective stepping, andhand contact strategies. The planner optimizes both the contact sequence andthe robot state trajectories. A high-level tree search is conducted toiteratively grow a contact transition tree. At each edge of the tree,trajectory optimization is used to calculate robot stabilization trajectoriesthat produce the desired contact transition while minimizing kinetic energy.Also, at each node of the tree, the optimizer attempts to find a self-motion(inertial shaping movement) to eliminate kinetic energy. This paper alsopresents an efficient and effective method to generate initial seeds tofacilitate trajectory optimization. Experiments demonstrate show that ourproposed algorithm can generate complex stabilization strategies for asimulated robot under varying initial pushes and environment shapes.

Unified Multi-Contact Fall Mitigation Planning for Humanoids via Contact Transition Tree Optimization