Numerical Integration and Dynamic Discretization in Heuristic Search Planning over Hybrid Domains
Miquel Ramirez, Enrico Scala, Patrik Haslum, Sylvie Thiebaux

TL;DR
This paper introduces FS+, a hybrid domain planner that combines numerical integration, dynamic discretization, and heuristic guidance to effectively handle both discrete and continuous changes without restrictive assumptions.
Contribution
The paper presents FS+, a novel hybrid planner that separates planning and simulation steps, enabling flexible handling of complex hybrid domains with global constraints.
Findings
FS+ effectively plans in diverse hybrid domains.
It handles continuous and discrete changes without restrictive assumptions.
The approach improves robustness over existing hybrid planners.
Abstract
In this paper we look into the problem of planning over hybrid domains, where change can be both discrete and instantaneous, or continuous over time. In addition, it is required that each state on the trajectory induced by the execution of plans complies with a given set of global constraints. We approach the computation of plans for such domains as the problem of searching over a deterministic state model. In this model, some of the successor states are obtained by solving numerically the so-called initial value problem over a set of ordinary differential equations (ODE) given by the current plan prefix. These equations hold over time intervals whose duration is determined dynamically, according to whether zero crossing events take place for a set of invariant conditions. The resulting planner, FS+, incorporates these features together with effective heuristic guidance. FS+ does not…
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Taxonomy
TopicsAI-based Problem Solving and Planning · Robotic Path Planning Algorithms · Logic, Reasoning, and Knowledge
