Robots can assist humans during a mission e.g. searching for victims in case of a catastrophe within dangerous environments as well as exploring areas for transportation of materials through rough terrain. A multi-agent system can speed up this process by working as distributed sensor system. Therefore the task is divided into subtasks each performed by an individual robot within the team.
For exploration of an unknown area a robot requires a positioning system and a data distribution network besides the sensor array. As test platform the Eddie robot equipped with an active optical sensor system (e.g. Microsoft Kinect) as well as additional IR and ultrasonic sensors is used. These sensors are used for environmental perception and obstacle detection. A WLAN-based network serves for the data distribution among the robots. Next to standard moving abilities the robot can to turn on it's vertical axis while maintaining position.
By giving all robots in the team equal HMI and environment perception capabilities a redundant system can be achieved. Furthermore by sharing information e.g. of parts of the environment which have already been explored over a private robot network can help avoiding multiple exploration resulting in increased efficiency: R2 moves towards area 3 instead of exploring area 2 where R1 is working). Meanwhile the operator may gives and distributes orders to the robot team.
For exchanging information regarding the surrounding area of the robots especially the 2D/3D information needs to be compressed due to communication channel limitations. To form a combined data structure of the environmental information of all robots it needs to be arrange with respect to the position and orientation of the individual robot. During this process a data compression by removing unnecessary redundancy is possible. Building a 3D panorama is one option for data reduction.