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The autonomous execution of manipulation tasks in unstructured, dynamic environments requires the consideration of various motion constraints. Any motion performed during the manipulation task has to satisfy constraints imposed by the task itself, but also has to consider kinematic and dynamic limitations of the manipulator, avoid unpredictably moving obstacles, and observe constraints imposed by the global connectivity of the workspace. Furthermore, the unpredictability of unstructured environments requires the continuous incorporation of feedback to reliably satisfy these constraints. We present a novel feedback motion planning approach, called elastic roadmap framework, capable of satisfying all of the motion constraints that arise in autonomous mobile manipulation and their respective feedback requirements. This framework is validated with simulation experiments using a mobile manipulation platform and a stationary manipulator.

Elastic Roadmaps: Globally Task-Consistent Motion for Autonomous Mobile Manipulation in Dynamic Environments