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Multi-Robot Object Transport Motion Planning with a Deformable Sheet
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Multi-Robot Object Transport Motion Planning with a Deformable Sheet
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Using a deformable sheet to handle objects is convenient and found in many practical applications. For object manipulation through a deformable sheet that is held by multiple mobile robots, it is a challenging task to model the object-sheet interactions. We present a computational model and algorithm to capture the object position on the deformable sheet with changing robotic team formations. A virtual variable cables model (VVCM) is proposed to simplify the modeling of the robot-sheet-object system. With the VVCM, we further present a motion planner for the robotic team to transport the object in a three-dimensional (3D) cluttered environment. Simulation and experimental results with different robot team sizes show the effectiveness and versatility of the proposed VVCM. We also compare and demonstrate the planning results to avoid the obstacle in 3D space with the other benchmark planner.
Forward citations
Cited by 1 Pith paper
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Shape Formation for the Cooperative Transportation of Arbitrary Objects Using Multi-Agent Reinforcement Learning
Multi-agent RL produces robot policies that form balanced supporting shapes under arbitrary objects for cooperative transport and generalize across cluttered scenes and complex geometries.
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