CMU talk: Differentially Constrained Motion Re-Planning

CMU FRC Seminar

Differentially Constrained Motion Re-Planning

Mihail Pivtoraiko
Graduate Student, Robotics Institute, CMU

Thursday, December 11th

Abstract
This talk presents an approach to differentially constrained robot motion planning and efficient re-planning. Satisfaction of differential constraints is guaranteed by the state lattice, a search space which consists of feasible motions. Any systematic re-planning algorithm, e.g. D*, can be utilized to search the state lattice to find a motion plan that satisfies the differential constraints, and to repair it efficiently in the event of a change in the environment. Further efficiency is obtained by varying the fidelity of representation of the planning problem. High fidelity is utilized where it matters most, while it is lowered in the areas that do not affect the quality of the plan significantly. The talk presents a method to modify the fidelity between re-plans, thereby enabling dynamic flexibility of the search space, while maintaining its compatibility with re-planning algorithms. The approach is especially suited for mobile robotics applications in unknown challenging environments. We successfully applied the motion planner to robot navigation in this setting.

Speaker Bio: Mihail Pivtoraiko, is a graduate student at the Robotics Institute. He received his Master's degree at the Robotics Institute in 2005 and worked in the Robotics Section at the NASA/Caltech Jet Propulsion Laboratory (JPL) before returning to RI. Mihail's interests include improving the performance and reliability of mobile robots through research in artificial intelligence and robot control. Over the past five years, he focused on off-road robot motion planning and navigation, and has participated in DARPA projects (PerceptOR, LAGR), as well as research projects at JPL .