The Multi-SRT method is a cooperative exploration strategy for a team of mobile robots. The method proceeds from the parallelization of the single-robot SRT technique and is based on the randomized incremental generation of a collection of data structures called Sensor-based Random Trees (SRT), each representing a roadmap of an explored area with an associated safe region. Decentralized cooperation and coordination mechanisms are used to improve the exploration efficiency and to avoid conflicts.
The Multi-SRG method is a decentralized cooperative exploration strategy for mobile robots. A roadmap of the explored area, with the associate safe region, is built in the form of a compact data structure, called Sensor-based Random Graph. This is incrementally expanded by the robots by using a randomized local planner which automatically realizes a trade-off between information gain and navigation cost. Connecting structures, called bridges, are incrementally added to the graph to create shortcuts and improve the connectivity of the roadmap. Decentralized cooperation and coordination mechanisms are used so as to guarantee exploration efficiency and avoid conflicts. Simulations are presented to show the performance of the proposed technique.
Documents
[1] A. Franchi, L. Freda, G. Oriolo, and M. Vendittelli, A Randomized Strategy for Cooperative Robot Exploration, in 2007 IEEE Int. Conf. in Robotics and Automation, Rome, Italy, Apr. 2007, pp. 768-774. (download)
[2] A. Franchi, L. Freda, G. Oriolo, and M. Vendittelli, A decentralized strategy for cooperative robot exploration, in Proceedings of the 1st international conference on Robot communication and coordination, Athens, Greece, Oct. 2007. (download)
[3] A. Franchi, L. Freda, Luca Marchionni, G. Oriolo, and M. Vendittelli, Decentralized cooperative exploration: Implementation and experiments, in Intelligent Autonomous Systems 10, Baden-Baden, Germany, Jul. 2008, pp. 348-355. (download)
[4] A. Franchi, L. Freda, G. Oriolo, and M. Vendittelli, The sensor-based random graph method for cooperative robot exploration, IEEE/ASME Transactions on Mechatronics, vol. 14, no. 2, pp. 163-175, 2009. (download)
Realized within the Move3D (a powerful motion planning software environment realized at LAAS-CNRS) under the assumption of perfect (although limited-range) sensing and localization, these simulation clips highlight the performance of the Multi-SRT method for cooperative robot exploration.
Simulation 1: scattered start (AVI clip, zipped). The robots are initially scattered in the environment (as if they had been parachuted).
Simulation 2: clustered start (AVI clip, zipped). The exploration is started with the robots grouped in a cluster (more realistic for environments with a single main entrance).
Note how the robots assume different colors during the exploration:
Realized within the Move3D (a powerful motion planning software environment realized at LAAS-CNRS) under the assumption of perfect (although limited-range) sensing and localization, these simulation clips highlight the performance of the Multi-SRG method for cooperative robot exploration.
Simulation 1: scattered start (AVI clip, zipped). The robots are initially scattered in the environment (as if they had been parachuted).
Simulation 2: clustered start (AVI clip, zipped). The exploration is started with the robots grouped in a cluster (more realistic for environments with a single main entrance).
Note how the robots assume different colors during the exploration:
Realized within our software under the assumption of limited communication range and perfect (although limited-range) sensing and localization, this simulation show the creation of local networks and the data exchanging process (AVI clip). The robots are initially scattered in the environment (as if they had been parachuted).
Conducted with a team of 4 Khepera III robots. A wireless card and a Hokuyo URG-04LX laser rangefinder has been added to the standard equipment of each robot.
Video: exploration of two environments (AVI clip).