# Accelerating Search-Based Planning for Multi-Robot Manipulation by Leveraging Online-Generated Experiences

arXiv: https://arxiv.org/abs/2404.00143 · HTML: https://mlsanity.com/paper/2404.00143/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- Builds on 11 of its 29 references that are in the map.
- First posted on arXiv 29 Mar 2024.

## Builds on (most cited first, 11 of 11)

- [Multi-Agent Pathfinding: Definitions, Variants, and Benchmarks](https://mlsanity.com/paper/1906.08291/) (2019)
- [Revisiting Fundamentals of Experience Replay](https://mlsanity.com/paper/2007.06700/) (2020)
- [Reducing the Barrier to Entry of Complex Robotic Software: a MoveIt! Case Study](https://mlsanity.com/paper/1404.3785/) (2014)
- [EECBS: A Bounded-Suboptimal Search for Multi-Agent Path Finding](https://mlsanity.com/paper/2010.01367/) (2020)
- [Motion Planning around Obstacles with Convex Optimization](https://mlsanity.com/paper/2205.04422/) (2022)
- [Representation-Optimal Multi-Robot Motion Planning using Conflict-Based Search](https://mlsanity.com/paper/1909.13352/) (2019)
- [dRRT*: Scalable and Informed Asymptotically-Optimal Multi-Robot Motion Planning](https://mlsanity.com/paper/1903.00994/) (2019)
- [Provably Constant-time Planning and Replanning for Real-time Grasping Objects off a Conveyor Belt](https://mlsanity.com/paper/2101.07148/) (2021)
- [Certified Polyhedral Decompositions of Collision-Free Configuration Space](https://mlsanity.com/paper/2302.12219/) (2023)
- [Constant-time Motion Planning with Anytime Refinement for Manipulation](https://mlsanity.com/paper/2311.00837/) (2023)
- [Effective Integration of Weighted Cost-to-go and Conflict Heuristic within Suboptimal CBS](https://mlsanity.com/paper/2205.11624/) (2022)

## Built on by (most cited first, 4 of 4)

- [Multi-Robot Motion Planning with Diffusion Models](https://mlsanity.com/paper/2410.03072/) (2024)
- [QD-MAPPER: A Quality Diversity Framework to Automatically Evaluate Multi-Agent Path Finding Algorithms in Diverse Maps](https://mlsanity.com/paper/2409.06888/) (2024)
- [Multi Graph Search for High-Dimensional Robot Motion Planning](https://mlsanity.com/paper/2602.12096/) (2026)
- [Conflict-Based Lazy Search for Fast Multi-Manipulator Planning](https://mlsanity.com/paper/2607.04124/) (2026)

## Abstract (arXiv)

An exciting frontier in robotic manipulation is the use of multiple arms at once. However, planning concurrent motions is a challenging task using current methods. The high-dimensional composite state space renders many well-known motion planning algorithms intractable. Recently, Multi-Agent Path-Finding (MAPF) algorithms have shown promise in discrete 2D domains, providing rigorous guarantees. However, widely used conflict-based methods in MAPF assume an efficient single-agent motion planner. This poses challenges in adapting them to manipulation cases where this assumption does not hold, due to the high dimensionality of configuration spaces and the computational bottlenecks associated with collision checking. To this end, we propose an approach for accelerating conflict-based search algorithms by leveraging their repetitive and incremental nature -- making them tractable for use in complex scenarios involving multi-arm coordination in obstacle-laden environments. We show that our method preserves completeness and bounded sub-optimality guarantees, and demonstrate its practical efficacy through a set of experiments with up to 10 robotic arms.