Learning by demonstration for co-operative navigation with assistive mobility devices
- Publication Type:
- Conference Proceeding
- Australasian Conference on Robotics and Automation, ACRA, 2015
- Issue Date:
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This work proposes a learning by demonstration framework for intuitive navigational adaptation of human-robot interactive mobile systems. Co-navigation algorithms for mobile robots tend to be highly parameterised with variables that may be difficult to manually con- figure to an individual user's desired behaviours by non-Technical personnel, e.g. carers and therapists overseing activities with would-be intelligent power mobility devices. The proposed framework automatically learns suitable joy- stick inputs for safe handling of the platform from a healthy user aware of a desired subset of behaviours (generic collision avoidance, wall- following and forward/reverse alignment manoeuvres) through performance of a small set of elementary training exercises, without the need and risk associated to trial-And-error vari\able tuning. The paper compares the semi-Autonomous capability of the proposed learning scheme with the popular Vector Field Histogram local planner in a corridor navigation task, showing its ability to safely generalise to different environments despite the simplicity of the training demonstrations.
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