Towards Combining HTN Planning and Geometric Task Planning
This work addresses the challenge of combining high-level and low-level planning in robotics, but it appears incremental as it builds on existing planning methods without introducing a fundamentally new paradigm.
The paper tackles the problem of integrating symbolic and geometric task planning by proposing an interface that allows geometric reasoning on abstract tasks, aiming for a more principled interaction and independent decision-making. It demonstrates how the planners can be interfaced and interleaved, with experimental results serving as a benchmark for future extensions.
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.