Expanding the Frontiers of Motion Planning: Feedback, Differential Constraints, and Resolution Completeness

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The field of motion planning has recently enjoyed numerous successes both in terms of understanding the critical issues and in applications throughout robotics and related fields. Its algorithms have found use in disparate areas such as humanoid robotics, automotive manufacturing, spacecraft navigation, architecture, computational geography, computer graphics, and computational biology. This project expands the basic motion-planning problem to include critical concerns that are not covered by the motionPlanning algorithms that are in widespread use. The work considers a combination of feedback, differential constraints, and resolution completeness, along with the traditional obstacle-avoidance concerns of motion planning. Long-term, broad impact is expected from this work by leveraging off of the successes of existing motion planning algorithms in applications. Educational impact will also arise through the training of doctoral students, the development of graduate-level courses, the involvement of undergraduates in research, and attempts to recruit women and minorities.