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AssemblyPRM: Assembly/Disassembly Sequencing Using a Motion Planning Approach
supported by NSF, Texas Higher Education Coordinating Board
Nancy Amato
Project Alumni: Sujay Sundaram, Ian Remmler
We propose a new approach for generating disassembly sequences. Our motion planning based approach treats the parts in the assembly as robots and operates in the composite configuration space of the parts' individual configuration spaces. Randomized techniques inspired by recent methods proposed for motion planning are used to sample configurations in this space.
Although a purely randomized approach to sampling is successful in systems with a small number of parts, typical assemblies consist of numerous parts and the corresponding composite C-spaces have high dimensionality. In such cases, a completely randomized sampling approach would be ineffective since many important configurations for the disassembly sequence will involve closely packed parts, i.e., the disassembly sequence will pass through narrow passages in the C-space.
Our solution to this problem is to bias the sampling by computing
potential movement directions based on the geometric characteristics
of configurations known to be reachable from the assembled
configuration (the start). For example, we select potential
directions which are perpendicular to part faces.
Thus, our disassembly algorithm constructs a disassembly tree
which is rooted at the starting assembled configuration.
Our experimental results with several non-trivial puzzle-like
assemblies show the potential of this approach.
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swap_naive: | Swapping two blocks using purely PRM approach. |
| swap_int: | Swapping two blocks using face normals as 'hints' for picking movement directions. | |
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puzzle: | Disassembly of a planar block puzzle. |
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puzzle_blocked: | Disassembly of the same puzzle but with all but one side obstructed. |
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puzzle3d: | Disassembly of a 10 piece 3D block puzzle. |
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pentomino: | Disassembly of 12 piece 'pentomino' puzzle. |
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