# Towards Combining HTN Planning and Geometric Task Planning

arXiv: https://arxiv.org/abs/1307.1482 · HTML: https://mlsanity.com/paper/1307.1482/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 4 Jul 2013.

## Built on by (most cited first, 3 of 3)

- [Multi-Stage Cable Routing through Hierarchical Imitation Learning](https://mlsanity.com/paper/2307.08927/) (2023)
- [MPTP: Motion-Planning-aware Task Planning for Navigation in Belief Space](https://mlsanity.com/paper/2104.04696/) (2021)
- [Spatial Reasoning via Deep Vision Models for Robotic Sequential Manipulation](https://mlsanity.com/paper/2306.17053/) (2023)

## Abstract (arXiv)

In this paper we present an interface between a symbolic planner and a geometric task planner, which is different to a standard trajectory planner in that the former is able to perform geometric reasoning on abstract entities---tasks. We believe that this approach facilitates a more principled interface to symbolic planning, while also leaving more room for the geometric planner to make independent decisions. We show how the two planners could be interfaced, and how their planning and backtracking could be interleaved. We also provide insights for a methodology for using the combined system, and experimental results to use as a benchmark with future extensions to both the combined system, as well as to the geometric task planner.