Back to Search
Start Over
Cloud-based improved Monte Carlo localization algorithm with robust orientation estimation for mobile robots.
- Source :
-
Engineering Computations . 2019, Vol. 36 Issue 1, p178-203. 26p. - Publication Year :
- 2019
-
Abstract
- 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. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 02644401
- Volume :
- 36
- Issue :
- 1
- Database :
- Academic Search Index
- Journal :
- Engineering Computations
- Publication Type :
- Academic Journal
- Accession number :
- 134612326
- Full Text :
- https://doi.org/10.1108/EC-03-2017-0081