Building volumetric maps with cooperative mobile robots and useful information sharing: a distributed control approach based on entropy
Project Type: PhD Project
Research Field: Cooperative Robotics
Time span: 09/2002-09/2005

Building cooperatively 3-D maps of unknown environments is one of the application fields of multi-robot systems. This on-going research addresses that problem through a probabilistic approach based on information theory.

A distributed cooperative architecture model has been formulated whereby robots exhibit cooperation through efficient information sharing and coordinated exploration. A probabilistic model of a 3-D map and a statistical sensor model are used to update the map upon range measurements, with an explicit representation of uncertainty through the definition of map's entropy. Each robot is able to build a 3-D map upon measurements from its own stereo-vision sensor and is committed to cooperate with other robots by sharing useful measurements. An entropy-based measure of information utility is used to define a cooperation strategy for sharing useful information, without overwhelming communication resources with redundant or unnecessary information. Each robot reduces the map's uncertainty by exploring maximum information viewpoints, while minimizing mutual information and interference with other robots, so that maximum information gain is achieved in every sensing cycle.

The proposed framework has been validated through experiments with a set of mobile robots equipped with stereo-vision sensors.

Related People

Jorge Dias
Rui P. Rocha