Cloud-based improved Monte Carlo localization algorithm with robust orientation estimation for mobile robots

I. hsum Li, Wei-Yen Wang, Chung Ying Li, Jia Zwei Kao, Chen Chien Hsu

研究成果: 雜誌貢獻文章同行評審

摘要

Purpose: This paper aims to demonstrate a cloud-based version of the improved Monte Carlo localization algorithm with robust orientation estimation (IMCLROE). The purpose of this system is to increase the accuracy and efficiency of indoor robot localization. Design/methodology/approach: The cloud-based IMCLROE is constructed with a cloud–client architecture that distributes computation between servers and a client robot. The system operates in two phases: in the offline phase, two maps are built under the MapReduce framework. This framework allows parallel and even distribution of map information to a cloud database in pre-described formats. In the online phase, an Apache HBase is adopted to calculate a pose in-memory and promptly send the result to the client robot. To demonstrate the efficiency of the cloud-based IMCLROE, a two-step experiment is conducted: first, a mobile robot implemented with a non-cloud IMCLROE and a UDOO single-board computer is tested for its efficiency on pose-estimation accuracy. Then, a cloud-based IMCLROE is implemented on a cloud–client architecture to demonstrate its efficiency on both pose-estimation accuracy and computation ability. Findings: For indoor localization, the cloud-based IMCLROE is much more effective in acquiring pose-estimation accuracy and relieving computation burden than the non-cloud system. Originality/value: The cloud-based IMCLROE achieves efficiency of indoor localization by using three innovative strategies: firstly, with the help of orientation estimation and weight calculation (OEWC), the system can sort out the best orientation. Secondly, the system reduces computation burden with map pre-caching. Thirdly, the cloud–client architecture distributes computation between the servers and client robot. Finally, the similar energy region (SER) technique provides a high-possibility region to the system, allowing the client robot to locate itself in a short time.

原文英語
頁(從 - 到)178-203
頁數26
期刊Engineering Computations (Swansea, Wales)
36
發行號1
DOIs
出版狀態已發佈 - 2019 二月 11

ASJC Scopus subject areas

  • Software
  • Engineering(all)
  • Computer Science Applications
  • Computational Theory and Mathematics

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