# Backward-Forward Search for Manipulation Planning

arXiv: https://arxiv.org/abs/1604.03468 · HTML: https://mlsanity.com/paper/1604.03468/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 12 Apr 2016.

## Built on by (most cited first, 2 of 2)

- [A Meta-Engine Framework for Interleaved Task and Motion Planning using Topological Refinements](https://mlsanity.com/paper/2408.05795/) (2024)
- [Optimistic Reinforcement Learning-Based Skill Insertions for Task and Motion Planning](https://mlsanity.com/paper/2510.14065/) (2025)

## Abstract (arXiv)

In this paper we address planning problems in high-dimensional hybrid configuration spaces, with a particular focus on manipulation planning problems involving many objects. We present the hybrid backward-forward (HBF) planning algorithm that uses a backward identification of constraints to direct the sampling of the infinite action space in a forward search from the initial state towards a goal configuration. The resulting planner is probabilistically complete and can effectively construct long manipulation plans requiring both prehensile and nonprehensile actions in cluttered environments.