The used memory data structure allows for a reduced search comple

The used memory data structure allows for a reduced search complexity of O(1), which combined with a Finite State Automata (FSA) allows us to demonstrate that our technique effectively distributes the robots over the environment and allows them to quickly accomplish their mission. This results in a hybrid http://www.selleckchem.com/products/Tubacin.html approach capable of fast, simple and computational efficient exploration. A series of simulated experiments were performed and analyzed, demonstrating the successful exploration of a 200 m2 area in about a minute with a team of three Pioneer-3DX robots at moderate driving and steering speeds and equipped essentially with a laser scanner. Additionally, successful results were demonstrated in real experiments with a team of two Jaguar V2 robots, also equipped with laser scanners, in a 20 m2 area geometrically similar to the simulation scenario.
One of the most interesting observations is that we achieved qualitatively similar navigation and robot distribution as in the literature but with a way simpler approach, using less computational power, and without any negotiation or mapping technique, at the only cost of sufficient localization so as to handle 1 m2 error.This paper is structured as follows: first, autonomous exploration approaches are detailed in Section 2; next we present our behaviors and FSA design in Section 3; Section 4 follows with the implemented experiments and results; and finally, we present in Section 5 a summary of contributions and conclusions, as well as our future directions.2.?Related WorkMany approaches have been proposed for exploring unknown environments with single and multiple robots.
A deep comparison on several autonomous exploration approaches has been reported in [22] including their main pros and cons. In most of these, the essence is to allow the robots to autonomously navigate to the best unexplored area. Area representation makes the main difference among different techniques. Nevertheless, a popular basis is the frontier-based exploration algorithm introduced by Yamauchi in [4].Main advantages of frontier exploration reside in that there is no world structure required, and that it is useful in cluttered environments and acceptable in large open spaces [23]. On the other hand, the necessity for robust localization and mapping impacts directly on algorithm complexity and the need for world representation.
Basically, the exploration cycle requires to: gather sensor data, share/merge evidence grids (maps), extract edges and match locations, allocate Cilengitide frontiers, and reliably navigate towards the allocated frontier.Concerning frontiers’ allocation, significant works have been proposed using market-based techniques. In [5] a successful multi-robot exploration is achieved with a bidding process. Enzalutamide clinical Nevertheless, the need for a central bid-evaluator agent is an undesired compromise.

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