2134/35356
Varuna De Silva
Varuna
De Silva
Jamie Roche
Jamie
Roche
Xiyu Shi
Xiyu
Shi
Ahmet Kondoz
Ahmet
Kondoz
IoT driven ambient intelligence architecture for indoor intelligent mobility
Loughborough University
2018
Ambient
Assistive
Autonomous
Intelligent
Mobility
Robot
Navigation
2018-10-17 10:49:17
Conference contribution
https://repository.lboro.ac.uk/articles/conference_contribution/IoT_driven_ambient_intelligence_architecture_for_indoor_intelligent_mobility/9464399
Personal robots are set to assist humans in their daily tasks. Assisted living is one of the major applications of personal assistive robots, where the robots will support health and wellbeing of the humans in need, especially elderly and disabled. Indoor environments are extremely challenging from a robot perception and navigation point of view, because of the ever-changing decorations, internal organizations and clutter. Furthermore, human-robot-interaction in personal assistive robots demands intuitive and human-like intelligence and interactions. Above challenges are aggravated by stringent and often tacit requirements surrounding personal privacy that may be invaded by continuous monitoring through sensors. Towards addressing the above problems, in this paper we present an architecture for "Ambient Intelligence" for indoor
intelligent mobility by leveraging IoTs within a framework of Scalable Multi-layered Context Mapping Framework. Our
objective is to utilize sensors in home settings in the least invasive manner for the robot to learn about its dynamic surroundings and interact in a human-like manner. The paper takes a semi-survey approach to presenting and illustrating preliminary results from our in-house built fully autonomous electric quadbike.