Abstract
The incorporation of service robots in human populated environments gives rise to the adaptation of cruise strategies that allow robots to move in a natural, secure and ordinary manner among their cohabitants. Therefore, robots should firstly apprehend their space similarly with the people and, secondly, should adopt human motion anticipation strategies in their planning mechanism. The paper at hand introduces a closed-loop human oriented robot navigation strategy, where on-board a moving robot, multimodal human detection and tracking methods are deployed to predict human motion intention in the shared workspace. The human occupied space is probabilistically constrained following the proxemics theory. The impact of human presence in the commonly shared space is imprinted to the robot’s navigation behaviour after undergoing a social filtering step based on the inferred walking pattern. The proposed method has been integrated with a robotic platform and extensively evaluated in terms of socially acceptable behaviour in real-life experiments exhibiting increased navigation capacity in human populated environments.
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Acknowledgments
This work has been supported by the EU Horizon 2020 funded project namely: “Robotic Assistant for MCI Patients at home (RAMCIP)” under the grant agreement with no: 643433.
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Kostavelis, I., Kargakos, A., Giakoumis, D., Tzovaras, D. (2017). Robot’s Workspace Enhancement with Dynamic Human Presence for Socially-Aware Navigation. In: Liu, M., Chen, H., Vincze, M. (eds) Computer Vision Systems. ICVS 2017. Lecture Notes in Computer Science(), vol 10528. Springer, Cham. https://doi.org/10.1007/978-3-319-68345-4_25
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DOI: https://doi.org/10.1007/978-3-319-68345-4_25
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