Constrained resolved acceleration control for humanoids

Resolved acceleration control is a well-known strategy used in tracking control of robotic systems where the desired motion is specified in task-space. Typically, such controllers are developed for systems which exhibit redundancy with respect to execution of operational tasks. While redundancy fundamentally adds new capabilities (self-motion and subtask performance capability), the degree to which secondary objectives can be faithfully executed cannot be determined in advance unless the motion is planned and the environment is known. Therefore, execution of secondary objectives cannot be guaranteed. In fact, a robot which exhibits redundancy with respect to operational tasks may have insufficient degrees of freedom to fulfill more critical objectives such as enforcing constraints. In this paper, we present a generalized constrained resolved acceleration control framework to handle execution of operational tasks and constraints for redundant and non-redundant task (and constraint) specifications. The approach is particularly well suited for online control of complex robot structures such as humanoid robots. The current formulation considers joint limit and collision constraints. The efficacy of the proposed algorithm is demonstrated by simulated experiments of task level upper-body human motion replication on the Honda humanoid robot.