Fall on Backpack: Damage Minimizing Humanoid Fall on Targeted Body Segment Using Momentum Control

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 the main threat to safety and smooth operation of humanoid robots, and thus it is critical to explore how to manage an unavoidable fall of humanoids. 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 re-orient 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 utilizing dynamic coupling, i.e., by rotating the swing leg aiming to generate spin rotation of the trunk (backpack), and by rotating the trunk backward to drive the trunk to touch down with the backpack. The planning and control algorithms for fall are demonstrated in simulation. INTRODUCTION As humanoid robots start to migrate from controlled laboratory environments to free and physically interactive surroundings ∗Address all correspondence to this author. containing objects and people, the issues of safety and robust operation of these robots will demand major attention from the research community. A catastrophic fall is perhaps the gravest threat to the safety and security of these robots and their surroundings. Yet, despite the stringent control that is imposed on every humanoid movement, fall remains an uncontrolled, understudied, and basically overlooked aspect of humanoid technology. Because of its complex dynamics and lack of well-defined theoretical tools, one is tempted to completely ignore the treatment of a humanoid fall. This, however, does nothing to reduce the chances of fall, but rather makes the effects of fall unpredictable and potentially more harmful. In a comparable situation involving automobiles, we have learned that crash studies can significantly improve the “crashworthiness” of a car by increasing the safety of both car occupants and outside pedestrians. Inspired by this, we deliberately focus our attention to the phenomenon of humanoid fall and attempt to develop a comprehensive control strategy to deal with this undesired and catastrophic event. During an accidental fall the humanoid controller may have two primary, and distinctly different, objectives: a) self-damage minimization and b) minimization of damage to other objects or people. If during the fall the robot can hit nearby objects or persons, its primary objective would be to prevent this from happening. The robot may try to achieve this by means of changing its default fall direction, as we have reported [1, 2]. If, however, the fall occurs in an open space, a self-damage minimization strategy 1 Copyright c © 2011 by ASME can attempt to reduce the harmful effects of the ground impact.