Abstract
The presence of children in a social assistive robotics context is particularly challenging for perception, mainly, in the task of locating them using inherently uncertain sensor data. This paper proposes a method for active perception with the goal of finding one target, e.g., a child wearing a RFID tag. This method is based on a particle-filter modeling a probability distribution of the position of the child. Negative measurements are used to update this probability distribution and an information-theoretic approach to determine optimal robot trajectories that maximize information gain while surveying the environment. We present preliminary results, in a real robot, to evaluate the approach.
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Messias, J., Acevedo, J.J., Capitan, J., Merino, L., Ventura, R., Lima, P.U. (2015). A Particle-Filter Approach for Active Perception in Networked Robot Systems. In: Tapus, A., André, E., Martin, JC., Ferland, F., Ammi, M. (eds) Social Robotics. ICSR 2015. Lecture Notes in Computer Science(), vol 9388. Springer, Cham. https://doi.org/10.1007/978-3-319-25554-5_45
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DOI: https://doi.org/10.1007/978-3-319-25554-5_45
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