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Humanoid Robotics Laboratory
Humanoid Robotics Laboratory
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ItemPush Planning for Object Placement on Cluttered Table Surfaces(Georgia Institute of Technology, 2011-09) Cosgun, Akansel ; Hermans, Tucker ; Emeli, Victor ; Stilman, MikeWe present a novel planning algorithm for the problem of placing objects on a cluttered surface such as a table, counter or floor. The planner (1) selects a placement for the target object and (2) constructs a sequence of manipulation actions that create space for the object. When no continuous space is large enough for direct placement, the planner leverages means-end analysis and dynamic simulation to find a sequence of linear pushes that clears the necessary space. Our heuristic for determining candidate placement poses for the target object is used to guide the manipulation search. We show successful results for our algorithm in simulation.
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ItemSampling Heuristics for Optimal Motion Planning in High Dimensions(Georgia Institute of Technology, 2011-09) Akgun, Baris ; Stilman, MikeWe present a sampling-based motion planner that improves the performance of the probabilistically optimal RRT* planning algorithm. Experiments demonstrate that our planner finds a fast initial path and decreases the cost of this path iteratively. We identify and address the limitations of RRT* in high-dimensional configuration spaces. We introduce a sampling bias to facilitate and accelerate cost decrease in these spaces and a simple node-rejection criteria to increase efficiency. Finally, we incorporate an existing bi-directional approach to search which decreases the time to find an initial path. We analyze our planner on a simple 2D navigation problem in detail to show its properties and test it on a difficult 7D manipulation problem to show its effectiveness. Our results consistently demonstrate improved performance over RRT*.