A Particle-Filter Approach for Active Perception in Networked Robot Systems
João V. Messias, José J. Acevedo, Jesús Capitán, Luís Merino, Rodrigo Ventura, Pedro U. Lima · Lecture notes in computer science · 2015
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. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.