Coordinating Robot Motion, Sensing, and Control in Plans LDRD Project Final Report

The goal of this project was to develop a framework for robotic planning and execution that provides a continuum of adaptability with respect to model incompleteness, model error, and sensing error. For example, dividing robot motion into gross-motion planning, fine-motion planning, and sensor-augmented control had yielded productive research and solutions to individual problems. Unfortunately, these techniques could only be combined by hand with ad hoc methods and were resticted to systems where all kinematics are completely modeled in planning. Our original intent was to develop methods for understanding and autonomously synthesizing plans that coordinate motion, sensing, and control. The project considered this problem from several perspectives. Results included (1) theoretical methods to combine and extend gross-motion and fine-motion planning; (2) preliminary work in flexible-object manipulation and an implementable algorithm for planning shortest paths through obstacles for the flee-end of an anchored cable; (3) development and implementation of a fast swept-body distance algorithm; and (4) integration of Sandia’s C-Space Toolkit geometry engine and SANDROS motion planner and improvements, which yielded a system practical for everyday motion planning, with path-segment planning at interactive speeds. Results (3) and (4) have either led to follow-on work or are being used in current projects, and we believe that (2) will eventually be also.