# Conflict-Based Lazy Search for Fast Multi-Manipulator Planning

arXiv: https://arxiv.org/abs/2607.04124 · HTML: https://mlsanity.com/paper/2607.04124/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 14 of its 36 references that are in the map.
- First posted on arXiv 5 Jul 2026.

## Builds on (most cited first, 14 of 14)

- [Batch Informed Trees (BIT*): Informed Asymptotically Optimal Anytime Search](https://mlsanity.com/paper/1707.01888/) (2017)
- [Sampling-Based Motion Planning: A Comparative Review](https://mlsanity.com/paper/2309.13119/) (2023)
- [Generalized Lazy Search for Robot Motion Planning: Interleaving Search and Edge Evaluation via Event-based Toggles](https://mlsanity.com/paper/1904.02795/) (2019)
- [dRRT*: Scalable and Informed Asymptotically-Optimal Multi-Robot Motion Planning](https://mlsanity.com/paper/1903.00994/) (2019)
- [Search-based Motion Planning for Quadrotors using Linear Quadratic Minimum Time Control](https://mlsanity.com/paper/1709.05401/) (2017)
- [A Unifying Formalism for Shortest Path Problems with Expensive Edge Evaluations via Lazy Best-First Search over Paths with Edge Selectors](https://mlsanity.com/paper/1603.03490/) (2016)
- [Lazy Receding Horizon A* for Efficient Path Planning in Graphs with Expensive-to-Evaluate Edges](https://mlsanity.com/paper/1803.04998/) (2018)
- [Manipulation Planning Among Movable Obstacles Using Physics-Based Adaptive Motion Primitives](https://mlsanity.com/paper/2102.04324/) (2021)
- [db-CBS: Discontinuity-Bounded Conflict-Based Search for Multi-Robot Kinodynamic Motion Planning](https://mlsanity.com/paper/2309.16445/) (2023)
- [Accelerating Search-Based Planning for Multi-Robot Manipulation by Leveraging Online-Generated Experiences](https://mlsanity.com/paper/2404.00143/) (2024)
- [Integrating Uncertainty-Aware Human Motion Prediction into Graph-Based Manipulator Motion Planning](https://mlsanity.com/paper/2405.09779/) (2024)
- [Lazy Lifelong Planning for Efficient Replanning in Graphs with Expensive Edge Evaluation](https://mlsanity.com/paper/2105.12076/) (2021)
- [Unconstraining Multi-Robot Manipulation: Enabling Arbitrary Constraints in ECBS with Bounded Sub-Optimality](https://mlsanity.com/paper/2405.01772/) (2024)
- [CBS-Budget (CBSB): A Complete and Bounded Suboptimal Search for Multi-Agent Path Finding](https://mlsanity.com/paper/2206.00130/) (2022)

## Abstract (arXiv)

Employing multiple manipulators can boost efficiency and accomplish tasks that a single manipulator cannot do. However, real-time planning for multiple manipulators in a cluttered workspace still poses significant challenges for planning algorithms. This article proposes a new planning algorithm called Conflict-Based Lazy Search (CBLS) for multimanipulator planning. CBLS is built on Conflict-Based Search (CBS), an efficient multiagent pathfinding (MAPF) algorithm that has shown an order of magnitude speedup over previous approaches [1], [2]. CBS addresses MAPF by solving many single-agent pathfinding (SAPF) problems. Thus, its planning time directly depends on the efficiency of the SAPF algorithm adopted. Our CBLS algorithm enhances CBS with precomputation and lazy search. First, a lazily evaluated graph with controlled sparsity is precomputed for a single manipulator. Second, we propose the Lazy Edged-based A* (LEA*) for efficient SAPF. Since edge evaluation is the computational bottleneck of manipulator planning, LEA* uses lazy search and an edge queue to reduce the number of edge evaluations. We show that LEA* is optimally vertex efficient and has improved edge efficiency compared to A*. We apply the proposed CBLS to multi-manipulator planning problems and show its superior performance by comparing it with CBS and a sampling-based algorithm, namely, RRT-Connect.