Late Autumn: LLM Agents Specialize a General Multi-Robot Planner for One Warehouse
- Published
- Source
- arXiv
- Paper number
- 1399
- Field
- Robotics
- arXiv ID
- 2611.02391
Key points
- LLM coding agents ran six autonomous research campaigns to specialize a 9.0k-line general multi-robot planner for one warehouse site.
- Every campaign's best patch raised throughput by 22–60% over the baseline, and the gains held on 20 unseen seeds.
- The agents rediscovered known MAPF mechanisms such as corridor-exit priorities, local guidance, and rollouts, and independent campaigns found the same bottleneck.
- The gains largely carried over to another layout, a larger fleet, and other service times, but mostly vanished under an outbound-heavy demand mix.
- The final patches are 0.7k–2.4k lines with a median improving step of 27 lines, so experts can review them commit by commit.
- Review found problems that the score misses, and some patches multiply planner compute by over 100×.
Paper links
External research summaries. These are not HDATF publications or measured product results.