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Robot motion planning and control is an essential component in creating autonomous systems that are able to execute high-level tasks for navigating and manipulating objects in challenging environments. Motion planning has led to active research over the past decades. Most of the research focused on the computational issue of generating feasible paths that lead the robot to a desired goal, while generally ignoring control concerns such as feedback, optimum, and uncertainty. The breakthrough achieved with sampling-based algorithms leads to effective techniques for hard, high-dimensional problems, and the recent improvements brought motion-planning algorithms closer to applicability in real problems. Nowadays, the practical interest of the state-of-the-art techniques is no longer restricted to robotics but extends to challenging problems arising in such diverse fields as graphics animation, virtual prototyping, and computational biology.
Date of Publication: March 2009