Towards Combining HTN Planning and Geometric Task Planning
Lavindra de Silva, Amit Kumar Pandey, Mamoun Gharbi, Rachid, Alami

TL;DR
This paper introduces an interface that combines hierarchical task network (HTN) planning with geometric task planning, enabling more flexible and principled integration of symbolic and geometric reasoning in planning systems.
Contribution
It presents a novel interface and methodology for integrating HTN planning with geometric task planning, allowing for interleaved planning and backtracking.
Findings
Proposed a new interface for combining symbolic and geometric planning.
Demonstrated interleaving of planning and backtracking between the two systems.
Provided experimental results as a benchmark for future research.
Abstract
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.
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Taxonomy
TopicsAI-based Problem Solving and Planning · Robotic Path Planning Algorithms · Semantic Web and Ontologies
