Fall on Backpack: Damage Minimization of Humanoid Robots by Falling on Targeted Body Segments

Abstract

Safety and robustness will become critical issues when humanoid robots start sharing human environments in the future. In physically interactive human environments, a catastrophic fall is a major threat to the safety and smooth operation of humanoid robots. It is, therefore, imperative that humanoid robots be equipped with a comprehensive fall management strategy. This paper deals with the problem of reducing the impact damage to a robot associated with a fall. A common approach is to employ damage-resistant design and apply impact-absorbing material to robot limbs, such as the backpack and knee, that are particularly prone to fall related impacts. In this paper, we select the backpack to be the most preferred body segment to experience an impact. We proceed to propose a control strategy that attempts to reorient the robot during the fall such that it impacts the ground with its backpack. We show that the robot can fall on the backpack even when it starts falling sideways. This is achieved by generating and redistributing angular momentum among the robot limbs through dynamic coupling. The planning and control algorithms for a fall are demonstrated in simulation.