Abstract-We present a decentralized cooperative exploration strategy for a team of mobile robots equipped with range finders. A roadmap of the explored area, with the associate safe region, is built in the form of a Sensor-based Random Graph (SRG). This is expanded by the robots by using a randomized local planner which automatically realizes a trade-off between information gain and navigation cost. The nodes of the SRG represent view configurations that have been visited by at least one robot, and are connected by arcs that represent safe paths. These paths have been actually traveled by the robots or added to the SRG to improve its connectivity. Decentralized cooperation and coordination mechanisms are used so as to guarantee exploration efficiency and avoid conflicts. Simulations and experiments are presented to show the performance of the proposed technique.

Abstract-We present a frontier-based modification of the SRT (Sensor-based Random Tree) method, a previously proposed probabilistic strategy for sensor-based exploration of unknown environments by a mobile robot. The idea is to improve the efficiency of the method by biasing the randomized generation of configurations towards unexplored areas. Effective implementations of this strategy are proposed for SRT-Ball and SRT-Star, two instances of the general SRT method corresponding to different perception attitudes and sensing equipments. Comparative simulations are presented to show the benefits of the proposed technique.

Abstmct-We present a method for sensor-based exploration of unknown environments by a mobile robot. The method is based on the randomized incremental generation of a data structure called Sensor-based Random Tree (SRT), which represents a roadmap of the explored area with an associated safe region. Different exploration strategies may be obtained by instantiating the general method with different perception techniques. Two such techniques are discussed: the first, conservative and particularly suited to noisy sensors, results in an exploration strategy called SRT-Ball. The second perception technique is more confident, and the corresponding strategy is called SRT-Star. The two strategies are critically compared by simulations as well as by experiments on the Magellanpro robot.

We provide key facts about the TRADR project deployment of ground and aerial robots in Amatrice, Italy, after the major earthquake in August 2016. The robots were used to collect data for 3D textured models of the interior and exterior of two badly damaged churches of high national heritage valu

Abstract-We present a cooperative exploration strategy for mobile robots. The method is based on the randomized incremental generation of a collection of data structures called Sensor-based Random Trees, each representing a roadmap of an explored area with an associated safe region. Decentralized cooperation and coordination mechanisms are introduced so as to improve the exploration efficiency and to avoid conflicts. Simulations in various environments are presented to show the performance of the proposed technique.