A cognitive collaborative multi-agent control architecture that addresses real-world control problems for swarms of mobile robots is proposed. The swarm's emergent behaviour is obtained by using a distributed Particle Swarm Optimization inspired algorithm. A swarm-user interface is also presented and offers a way for a human operator to interact with and guide the robotic swarm without limiting its emergent intelligence. The architecture is designed as a multi-agent system developed using JADE Framework. Three types of agents were defined: local behaviour agent, social behaviour agent and graphical user interface (GUI) agent. Each robot is associated with a pair of a local and a social behaviour agents which implement the reactive component and the interaction between the robots. The swarm forms a hierarchical structure composed of subswarms and neighbourhoods based on tasks and goals defined by the user or the swarm itself. The GUI agent is used as a link between the human expert and the swarm. The architecture was tested on a swarm of e-puck robots.
Ecology is a challenging application area for mobile service robots. They should be able to automate tasks that are too tedious or dangerous for humans to execute, such as collecting waste material. Such a robot must make use of several senses, of which the most important and difficult to implement is vision. This paper presents the cognitive vision system of ReMaster One, an autonomous service robot that is able to recognize and sort waste in an indoor environment. A first prototype has been built and tested with success.