robotics
Six Robots Negotiate Rent on Shared Space
WarpWeaver grows local command trees and prices contested regions so decentralized planners can approach a certified agreement before the clock runs out.
Summary
WarpWeaver grows local command trees and prices contested regions so decentralized planners can approach a certified agreement before the clock runs out.
Joint optimal control for multiple nonlinear robots is usually centralized and offline, while real-time decentralized planners emphasize collision avoidance rather than the joint optimum. WarpWeaver replaces coupling with local constraints, grows dispersive command trees onboard and uses decentralized column generation to negotiate rents on shared space. At quiescence, the resulting agreement carries a near-optimality certificate; under deadlines, the asynchronous loop returns the best agreement reached so far. In simulation, the authors report travel-time reductions up to 22 percent against centralized offline planners and up to 37 percent against a decentralized real-time baseline, plus hardware experiments on six robots. The gains are benchmark- and scenario-specific and do not certify optimality when negotiation stops early.
Why it matters
WarpWeaver grows local command trees and prices contested regions so decentralized planners can approach a certified agreement before the clock runs out.
Limits and context
- The gains are benchmark- and scenario-specific and do not certify optimality when negotiation stops early.
Key claims
WarpWeaver grows local command trees and prices contested regions so decentralized planners can approach a certified agreement before the clock runs out.
Qualification: The gains are benchmark- and scenario-specific and do not certify optimality when negotiation stops early.
Evidence: source-2026-10-25-006
Sources
- arXiv preprint 2610.31540, original v1arXiv · primary research
Corrections
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