MOBOT

Intelligent Active Mobility Assistance Robot integrating Multimodal Sensory Processing

MOBOT – Intelligent Active MObility Assistance RoBOT integrating Multimodal Sensory Processing, Proactive Autonomy and Adaptive Interaction

MOBOT is an EU Framework 7 funded project aimed at developing two intelligent robotic platforms that can provide advanced mobility assistance to older or mobility impaired people. The project is coordinated by UWE’s Angelika Peer who leads a consortium of eight European partners from five countries.

Mobility disabilities are prevalent in our ageing society and impede activities important for the independent living of elderly people and their quality of life. MOBOT project is about supporting human mobility and thus enforcing fitness and vitality by developing intelligent robotic platforms designed to provide user-centred and natural support for ambulating in indoor environments. We envision the design of cognitive mobile robotic systems that can monitor and understand specific forms of human activity, in order to deduce what the human needs are, in terms of mobility. The goal is to provide user- and context-adaptive active support and ambulation assistance to elderly users, and generally to individuals with specific forms of moderate to mild walking impairment.

To achieve such a goal for the development of an efficient and intelligent robotic assistant, a variety of multimodal interaction and cognitive control functionalities must be embedded, so that the robot can autonomously reason about how to provide optimal support to the user whenever and wherever needed. In particular, MOBOT aims to design and deliver a cognitive mobility-aid robot that can act both:

  1. proactively, by realizing autonomous and context-specific monitoring of human activities and by subsequently reasoning on meaningful user behavioural patterns; and
  2. adaptively and interactively, by analysing multi-sensory and physiological signals related to gait and postural stability, and by performing adaptive compliance control for optimal physical support and active fall prevention.

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Page last updated 12 May 2016

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