Robust, Adaptive and Dynamic Robotic Motion Planning

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Research is to be conducted in several key areas of robotic movement planning. The emphasis is on robot motion planning algorithms for autonomous robots. A principal focus is on the investigation of motion planning problems with incomplete information or changing information about the environment, requiring the motion planning algorithm to be adaptive. Moreover, the research considers movement problems with inherent errors in the sensing and control, so the motion planning algorithms must be robust to a lack of information on the position of the robot, and if possible the algorithms must be minimal: that is use the least possible amount of information about the robot position and environment. The investigations will also consider motion planning problems in environments which are dynamically changing; these will require dynamic algorithms that respond to changing inputs. The research will involve solving motion planning problems using new formulations that have not yet been fully investigated. The research will concentrate particularly in emerging new areas in robotic movement planning that impact most strongly the overall goals of adaptive, robust, minimal, and dynamic robotic algorithms. Examples of topics to be researched are on-line planning algorithms for unknown environments which are randomized and/or may dynamically learn probabilistic models of the environment, and pursuit movement games (which involve movement planning with an adversary).