Competitive Task Allocation with Temporal Proposal Windows a
Overview
Source roundup from published reports. Claims below are attributed to their publishers, not independently verified. arXiv Robotics — research abstracts: 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…
Generated from attributed reports · Updated 36 minutes ago
Event evidence and corrections
0 attributed source owners. Ownership does not establish independent confirmation. Quantities are reported separately and are never added together.
Reported quantity · planning time reduction: 9 other · Basis not reported
“ducing planning time by up to 9 times and execution makespan by approximately 40%.”
Exact source · revision 1Source owner not reported
Reported quantity · number of MuJoCo environments: 14 other · Basis not reported
“ther a discovery needs a replan. If replanning is needed, the robot executes unaffected actions while the FM synthesizes corrective actions. These actions are inserted into the existing plan based on urgency, either executed immediately or deferred while preserving the remaining plan. We evaluate Robust-TAMP on 14 MuJoCo environments with hidden objects, blocked placements, articulated containers, and multi-step task”
Exact source · revision 1Source owner not reported
Artifact availability · code: available
“s that in-context examples help the planner follow multi-step procedures that zero-shot prompting struggles with. Our implementation code and project details are available at https://narendhiranv04.github.io/ROBUST-TAMP/.”
Exact source · revision 1Source owner not reported
Report timeline
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- arXiv Robotics — research abstractsDual-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.
- arXiv Robotics — research abstractsDeciding If, When, and Where to Replan for Robust Manipulation
This research proposes Robust-TAMP, a task and motion planning framework that dynamically decides whether to replan during manipulation tasks. The method improves success rates in both simulated and real-world environments, outperforming existing baselines by 47.1 percentage points. The framework allows for inserting corrective actions into existing plans based on urgency, and the study shows that in-context examples help planners follow multi-step procedures more effectively.
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