Dynamic balancing and flexible task execution for dynamic bipedalwalking machines

Abstract

Effective use of robots in unstructured environments requires that they have sufficient autonomy and agility to execute task-level commands with temporal constraints successfully. A challenging example of such a robot is a bipedal walking machine, particularly one of humanoid form. Key features of the human morphology include a variable base of support and a high center of mass. The high center of mass supports the ability to support a high “sensor package”; when standing erect, the head can see over obstacles. The variable base of support allows both for operation in tight spaces, by keeping the feet close together, and stability against disturbances, by keeping the feet further apart to widen the support base. The feet can also be placed in specific locations when there are constraints due to challenging terrain. Thus, the human morphology supports a range of capabilities, and is important for operating in unstructured environments as humans do. A bipedal robot with human morphology should be able to walk to a particular location within a particular time, while observing foot placement constraints, and avoiding a fall, if this is physically possible. This is a challenging problem because a biped is highly nonlinear and has limited actuation due to its limited base of support. This chapter describes a novel approach to solving this problem that incorporates three key components: (1) a robust controller that is able to use angular momentum to enhance controllability beyond the limits imposed by the support base; (2) a plan specification where task requirements are expressed in a qualitative form that provides for spatial and temporal execution flexibility; and (3) a task executive that compiles the plan into a form that makes the dynamic limitations explicit, and then executes the compiled form using the robust controller.