Dual-arm Cooperation for Tabletop Wiping with Temporal Object Removal
Dual-arm Cooperation for Tabletop Wiping with Temporal Object Removal
This research proposes a dual-arm cooperative planning framework for wiping table surfaces in the presence of scattered objects. The framework assigns one arm to rearrange objects while the other performs coverage wiping, enabling access to previously obstructed regions. The approach integrates Geo-MILP for task planning and KOMO for motion generation, achieving significant improvements in time efficiency and coverage compared to TAMP baselines.
Source: arXiv Robotics — research abstracts · Read original article ↗
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Publisher-reported claims, with original evidence. These results have not been independently verified by RoboSignal.
Reported numbers
planning time reduction
≤9
View original evidence
ducing planning time by up to 9 times and execution makespan by approximately 40%.
Open source S5
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ducing planning time by up to 9 times and execution makespan by approximately 40%.
Open source S5
ween wiping and object rearrangement. We then employ K-Order Markov Optimization (KOMO) to generate smooth, collision-free motions to ensure feasible execution. Simulation and physical experiments demonstrate that the proposed framework not only increases reachable coverage by enabling access to obstructed areas, but also significantly improves time efficiency compared to Task and Motion Planning (TAMP) baselines, re
Open source S4
regions. Specifically, we first construct a set of wiping and object-rearrangement action primitives. Based on these primitives, we introduce Geo-MILP, a geometry-aware task planner formulated as Mixed-Integer Linear Programming (MILP). By integrating Logic-Based Benders Decomposition (LBBD), Geo-MILP iteratively optimizes action sequencingand timing to resolve geometric conflicts, promoting efficient cooperation bet
Open source S3
Source：arXiv Robotics — research abstracts · arxiv.org