Robotic Motion Planning in Dynamic, Cluttered, Uncertain Environments

This paper presents a strategy for planning robot motions in dynamic, cluttered, and uncertain environments. Successful and efficient operation in such environments requires reasoning about the future system evolution and the uncertainty associated with obstacles and moving agents in the environment. This paper presents a novel procedure to account for future information gathering (and the quality of that information) in the planning process. After first presenting a formal Dynamic Programming (DP) formulation, we present a Partially Closed-loop Receding Horizon Control algorithm whose approximation to the DP solution integrates prediction, estimation, and planning while also accounting for chance constraints that arise from the uncertain location of the robot and other moving agents. Simulation results in simple static and dynamic scenarios illustrate the benefit of the algorithm over classical approaches.