Disney trains robots to fall, roll, and land safely without damage

Disney researchers, collaborating with university engineers, have developed a reinforcement learning-based system that enables bipedal robots to fall safely by controlling their landing poses to protect sensitive components. Traditional robots often suffer damage from uncontrolled falls due to stiff joints or flailing limbs, leading to costly repairs. Instead of resisting gravity, the new approach teaches robots to absorb impacts by rolling or shifting limbs during a fall to land in stable, damage-minimizing positions, prioritizing damage prevention over strict balance control. The training involved thousands of simulated falls with randomized velocities and directions, allowing the robot to learn a variety of safe landing strategies. A scoring system rewarded moves that reduced impact forces and protected vulnerable parts like the head and battery pack, while penalizing erratic motions. The researchers generated 24,000 stable poses, including artist-designed ones within realistic joint limits, to expand the robot’s repertoire of safe landings. After two days of training on powerful GPUs, the learned policy was transferred to a real 16-kil