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A local user mapping architecture for social robots
- Source :
- International Journal of Advanced Robotic Systems, Vol 14 (2017)
- Publication Year :
- 2017
- Publisher :
- SAGE Publishing, 2017.
-
Abstract
- User detection, recognition, and tracking is at the heart of human–robot interaction, and yet, to date, no universal robust method exists for being aware of the people in a robot’s surroundings. The present article imports into existing social robotic platforms different techniques, some of them classical, and other novel, for detecting, recognizing, and tracking human users. The outputs from the parallel execution of these algorithms are then merged, creating a modular, expandable, and fast architecture. This results in a local user mapping through fusion of multiple user recognition techniques. The different people detectors comply with a common interface called PeoplePoseList Publisher, while the people recognition algorithms meet an interface called PeoplePoseList Matcher. The fusion of all these different modules is based on the Unscented Kalman Filtering technique. Extensive benchmarks of the subcomponents and of the whole architecture demonstrate the validity and interest of all levels of the architecture. In addition, all the software and data sets generated in this work are freely available.
- Subjects :
- 0209 industrial biotechnology
Social robot
Computer science
lcsh:Electronics
lcsh:TK7800-8360
02 engineering and technology
lcsh:QA75.5-76.95
Computer Science Applications
020901 industrial engineering & automation
Website architecture
Artificial Intelligence
Human–computer interaction
0202 electrical engineering, electronic engineering, information engineering
Robot
020201 artificial intelligence & image processing
Tracking (education)
lcsh:Electronic computers. Computer science
Architecture
Software
Subjects
Details
- Language :
- English
- ISSN :
- 17298814
- Volume :
- 14
- Database :
- OpenAIRE
- Journal :
- International Journal of Advanced Robotic Systems
- Accession number :
- edsair.doi.dedup.....d2bf110cd555b9ffe8e4b3dd31cde166