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

作者：

Highlights：

• Motion planning is an essential task for an autonomous vehicle.

• Traditional motion planning algorithms ignore experience when serving new queries.

• Experience-based algorithms use multiple thread execution for serving queries.

• Motion planning belongs to P-SPACE hard problem class.

• Case-based reasoning is an AI approach for problem-solving using stored experiences.

摘要

•Motion planning is an essential task for an autonomous vehicle.•Traditional motion planning algorithms ignore experience when serving new queries.•Experience-based algorithms use multiple thread execution for serving queries.•Motion planning belongs to P-SPACE hard problem class.•Case-based reasoning is an AI approach for problem-solving using stored experiences.

论文关键词：Sampling-based algorithms,Experience-based algorithms,Case-Based reasoning,Artificial intelligence

论文评审过程：Received 1 June 2018, Revised 20 August 2018, Accepted 21 August 2018, Available online 23 August 2018, Version of Record 2 September 2018.

论文官网地址：https://doi.org/10.1016/j.eswa.2018.08.035