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Abstract

A key goal in robotics is to enable autonomous motion for mobile robots in a real world dynamic environment with unknown obstacles. This problem requires bringing together state-of-the-art algorithms in path planning, robot control, and perception. An additional challenge is that systems that implement these algorithms must be carefully implemented with sophisticated software techniques.This dissertation addresses the problem by expanding the Real-time Adaptive Motion Planning (RAMP) framework to enable real-time generation and execution of non-holonomic robot motion based on real-time perception of unknown dynamic obstacles in the presence of sensing and robot motion uncertainties. This dissertation further addresses how to systematically and rigorously test the implemented, integrated RAMP system to ensure robustness and reliability using state-of-the-art techniques in software testing.

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