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Humanoid Robotics Laboratory
Humanoid Robotics Laboratory
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ItemPath Planning Among Movable Obstacles: A Probabilistically Complete Approach(Georgia Institute of Technology, 2008) van den Berg, Jur ; Stilman, Mike ; Kuffner, James ; Lin, Ming ; Manocha, DineshIn this paper we study the problem of path planning among movable obstacles, in which a robot is allowed to move the obstacles if they block the robot's way from a start to a goal position. We make the observation that we can decouple the computations of the robot motions and the obstacle movements, and present a probabilistically complete algorithm, something which to date has not been achieved for this problem. Our algorithm maintains an explicit representation of the robot's configuration space. We present an efficient implementation for the case of planar, axis-aligned environments and report experimental results on challenging scenarios.
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ItemManipulation Planning Among Movable Obstacles.(Georgia Institute of Technology, 2007-04) Stilman, Mike ; Schamburek, Jan-Ullrich ; Kuffner, James ; Asfour, TaminThis paper presents the ResolveSpatialConstraints (RSC) algorithm for manipulation planning in a domain with movable obstacles. Empirically we show that our algorithm quickly generates plans for simulated articulated robots in a highly nonlinear search space of exponential dimension. RSC is a reverse-time search that samples future robot actions and constrains the space of prior object displacements. To optimize the efficiency of RSC, we identify methods for sampling object surfaces and generating connecting paths between grasps and placements. In addition to experimental analysis of RSC, this paper looks into object placements and task-space motion constraints among other unique features of the three dimensional manipulation planning domain.