AIJan 1, 2017

STRIPS Planning in Infinite Domains

arXiv:1701.00287v26 citations
Originality Incremental advance
AI Analysis

This addresses planning challenges in robotics for domains with infinite or continuous features, though it appears incremental as an extension of existing STRIPS methods.

The paper tackles the problem of robotic planning with continuous actions and non-linear constraints by introducing STRIPStream, an extension of the STRIPS language that uses blackbox generators to handle complex constraints, and demonstrates it on a high-dimensional robotic task and motion planning domain.

Many robotic planning applications involve continuous actions with highly non-linear constraints, which cannot be modeled using modern planners that construct a propositional representation. We introduce STRIPStream: an extension of the STRIPS language which can model these domains by supporting the specification of blackbox generators to handle complex constraints. The outputs of these generators interact with actions through possibly infinite streams of objects and static predicates. We provide two algorithms which both reduce STRIPStream problems to a sequence of finite-domain planning problems. The representation and algorithms are entirely domain independent. We demonstrate our framework on simple illustrative domains, and then on a high-dimensional, continuous robotic task and motion planning domain.

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