Speeding up single-query sampling-based algorithms using case-based reasoning

摘要

We present an extension to the single-query sampling-based algorithm for improving its response time using Case-Based Reasoning (CBR) technique. Unlike traditional experience-based planners, CBR depends on a single thread execution which reduces the required computation power. Additionally, it is always biased towards exploration rather than exploitation to overcome experience-based algorithms drawbacks. Results indicate that CBR extension has significantly improved sampling-based response time for similar served queries. (C) 2018 Elsevier Ltd. All rights reserved.