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CLARC: A Cognitive Robot for Helping Geriatric Doctors in Real Scenarios

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ROBOT 2017: Third Iberian Robotics Conference (ROBOT 2017)


Comprehensive Geriatric Assessment (CGA) is an integrated clinical process to evaluate the frailty of elderly persons in order to create therapy plans that improve their quality of life. For robotizing these tests, we are designing and developing CLARC, a mobile robot able to help the physician to capture and manage data during the CGA procedures, mainly by autonomously conducting a set of predefined evaluation tests. Built around a shared internal representation of the outer world, the architecture is composed of software modules able to plan and generate a stream of actions, to execute actions emanated from the representation or to update this by including/removing items at different abstraction levels. Percepts, actions and intentions coming from all software modules are grounded within this unique representation. This allows the robot to react to unexpected events and to modify the course of action according to the dynamics of a scenario built around the interaction with the patient. The paper describes the architecture of the system as well as the preliminary user studies and evaluation to gather new user requirements.

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This work has been partially funded by the EU ECHORD++ project (FP7-ICT-601116) and the TIN2015-65686-C5-1-R (MINECO and FEDER funds). Javier García is partially supported by the Comunidad de Madrid (Spain) funds under the project 2016-T2/TIC-1712. The authors warmly thank the members of the “Amis du Living Lab” community for their participation in this research.

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Correspondence to Dimitri Voilmy .

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Voilmy, D. et al. (2018). CLARC: A Cognitive Robot for Helping Geriatric Doctors in Real Scenarios. In: Ollero, A., Sanfeliu, A., Montano, L., Lau, N., Cardeira, C. (eds) ROBOT 2017: Third Iberian Robotics Conference. ROBOT 2017. Advances in Intelligent Systems and Computing, vol 693. Springer, Cham.

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-70832-4

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