Planning for Robust Execution of Humanoid Motions using Future Perceptive Capability

Abstract

We present an approach to motion planning for highly articulated systems that aims to ensure robust execution by augmenting the planning process to reason about the robot's ability to successfully perceive its environment during operation. By simulating the robot's perception system during search, our planner generates a metric, the so-called perceptive capability, that quantifies the `sensability' of the environment in each state given the task to be accomplished. We have applied our method to the problem of planning robust autonomous manipulations as performed by a humanoid robot in a kitchen environment. Our results indicate that reasoning about the future perceptive capability has the potential to greatly facilitate any task requiring visual feedback during control of the robot manipulator and can thus ensure higher task success rates than perception-unaware planning.