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Foraging has been identified as a benchmark for collective robotics. It consists on exploring an area and gathering prespecified objects from the environment. In addition to efficiently exploring an area, foragers have to be able to find special targets which are common to the whole population. This work proposes a method to cooperatively perform this(More)
Activity recognition has recently gained a lot of interest and there already exist several methods to detect human activites based on wearable sensors. Most of the existing methods rely on a database of labelled activities that is used to train an offline activity recognition system. This paper presents an approach to build an online activity recognition(More)
— The Ubichip is a reconfigurable digital circuit with special bio-inspired mechanisms that supports dynamic partial reconfigurability in a flexible and efficient way. This paper presents an adaptive size neural network model with incremental learning that exploits these capabilities by creating new neurons and connections whenever it is needed and by(More)
Foraging is a common benchmark problem in collective robotics in which a robot (the forager) explores a given environment while collecting items for further deposition at specific locations. A typical real-world application of foraging is garbage collection where robots collect garbage for further disposal in pre-defined locations. This work proposes a(More)