AILOROJul 29, 2013

ReAct! An Interactive Tool for Hybrid Planning in Robotics

arXiv:1307.7494v123 citations
Originality Synthesis-oriented
AI Analysis

This tool addresses the challenge for robotic researchers in handling sophisticated planning tasks, though it appears incremental as it builds on existing automated reasoners and formalisms.

The paper tackles the problem of simplifying high-level reasoning for robotics by introducing ReAct!, an interactive tool that allows researchers to describe robot actions and solve planning problems without needing expertise in underlying formalisms, enabling representation of complex hybrid domains and integration with automated reasoners.

We present ReAct!, an interactive tool for high-level reasoning for cognitive robotic applications. ReAct! enables robotic researchers to describe robots' actions and change in dynamic domains, without having to know about the syntactic and semantic details of the underlying formalism in advance, and solve planning problems using state-of-the-art automated reasoners, without having to learn about their input/output language or usage. In particular, ReAct! can be used to represent sophisticated dynamic domains that feature concurrency, indirect effects of actions, and state/transition constraints. It allows for embedding externally defined calculations (e.g., checking for collision-free continuous trajectories) into representations of hybrid domains that require a tight integration of (discrete) high-level reasoning with (continuous) geometric reasoning. ReAct! also enables users to solve planning problems that involve complex goals. Such variety of utilities are useful for robotic researchers to work on interesting and challenging domains, ranging from service robotics to cognitive factories. ReAct! provides sample formalizations of some action domains (e.g., multi-agent path planning, Tower of Hanoi), as well as dynamic simulations of plans computed by a state-of-the-art automated reasoner (e.g., a SAT solver or an ASP solver).

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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