An integrated decision making approach for adaptive shared control of mobility assistance robots

Geravand, M., Werner, C., Hauer, K. and Peer, A. (2016) An integrated decision making approach for adaptive shared control of mobility assistance robots. International Journal of Social Robotics, 8 (5). pp. 631-648. ISSN 1875-4791 Available from:

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Mobility assistance robots (MARs) provide support to elderly or patients during walking. The design of a safe and intuitive assistance behavior is one of the major challenges in this context. We present an integrated approach for the context-specific, on-line adaptation of the assistance level of a rollator-type mobility assistance robot by gain-scheduling of low-level robot control parameters. A human-inspired decision-making model, the Drift-Diffusion Model, is introduced as the key principle to gain-schedule parameters and with this to adapt the provided robot assistance in order to achieve a human-like assistive behavior. The mobility assistance robot is designed to provide a) cognitive assistance to help the user following a desired path towards a predefined destination as well as b) sensorial assistance to avoid collisions with obstacles while allowing for an intentional approach of them. Further, the robot observes the user long-term performance and fatigue to adapt the overall level of c) physical assistance provided. For each type of assistance a decision-making problem is formulated that affects different low-level control parameters. The effectiveness of the proposed approach is demonstrated in technical validation experiments. Moreover, the proposed approach is evaluated in a user study with 35 elderly persons. Obtained results indicate that the proposed gain-scheduling technique incorporating ideas of human decision-making models shows a general high potential for the application in adaptive shared control of mobility assistance robots.

Item Type:Article
Additional Information:The final publication is available at Springer via
Uncontrolled Keywords:mobility assistance robot, adaptive shared control, decision making
Faculty/Department:Faculty of Environment and Technology > Department of Engineering Design and Mathematics
ID Code:29151
Deposited By: Professor A. Peer
Deposited On:15 Jun 2016 14:17
Last Modified:08 Jun 2017 00:42

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