Abstract. We present a navigation and planning system using vision for extracting non predefined landmarks, a dead-reckoning system generating the integrated movement and a topological map. Localisation and planning remain possible even if the map is partially unknown. An omnidirectional camera gives a panoramic images from which unpredefined landmarks are extracted. The set of landmarks and their azimuths relative to a fixed orientation defines a particular location without any need of an external environment map. Transitions between two locations recognized at time t and t-1 are explicitly coded, and define spatio-temporal transitions. These transitions are the sensory-motor unit chosen to support planning. During exploration, a topological map (our cognitive map) is learned on-line from these transitions without any cartesian coordinates nor occupancy grids. The edges of this map may be modified in order to take into account dynamical changes of the environment. The transitions are linked with the integrated movement used for moving from one place to the others. When planning is required, the activities of transitions coding for the required goal in the cognitive map are enough to bias predicted transitions and to obtain the required movement.
Starting from neurobiological hypotheses on the existence of place cells (PC) in the brain, the aim of this article is to show how little assumptions at both individual and social levels can lead to the emergence of non-trivial global behaviors in a multi-agent system (MAS). In particular, we show that adding a simple, hebbian learning mechanism on a cognitive map allows autonomous, situated agents to adapt themselves in a dynamically changing environment, and that even using simple agent-following strategies (driven either by similarities in the agent movement, or by individual marks - “signatures” - in agents) can dramatically improve the global performance of the MAS, in terms of survival rate of the agents. Moreover, we show that analogies can be made between such a MAS and the emergence of certain social behaviors.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.