pith:BTREPN7Z
Multi-Agent Cooperative Transportation: Optimal and Efficient Task Allocation and Path Finding
The CT-TCBS algorithm with incremental expansion solves cooperative multi-robot transport by pruning the dominant search space for team assignments while integrating collision-free paths.
arxiv:2605.16097 v1 · 2026-05-15 · cs.MA
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Claims
Our comprehensive empirical evaluation demonstrates three key findings: (1) the incremental expansion strategy significantly outperforms the naive combinatorial approach by successfully pruning the dominant task-allocation search space.
The assumption that the incremental expansion strategy can reliably prune the task-allocation search space while preserving optimality, which is presented as a central empirical result but depends on the specific conflict-resolution heuristics chosen for the integrated CT-TAPF setting.
Formalizes CT-TAPF problem and introduces CT-TCBS optimal solver using incremental expansion for team formation plus task-centric sub-optimal solvers that improve efficiency over agent-centric baselines.
References
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| First computed | 2026-05-20T00:01:52.473352Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
0ce247b7f979ef513e08933fcedfa8a3004a3106606c0f27063dbb6b18d6891d
Aliases
· · · · ·Agent API
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Canonical record JSON
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