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We propose a distributed random algorithm to search a three dimensional environment by a network of mobile sensors. The presented algorithm utilizes an optimal three dimensional grid pattern for the search. To minimize the time of search, each mobile sensor shares the search information with the other sensors passing within its communication range. At first, mobile sensors build a covering grid, then they randomly move to the vertices of the covering grid to do the search task. A mathematically rigorous proof of convergence with probability 1 of the proposed algorithm is given and the effectiveness of the proposed search algorithm is demonstrated by simulations.

SUMMARYIn this paper, we present a novel algorithm for exploring an unknown environment using a team of mobile robots. The suggested algorithm is a grid-based search method that utilizes a triangular pattern which covers an area so that exploring the whole area is guaranteed. The proposed algorithm consists of two stages. In the first stage, all the members of the team make a common triangular grid of which they are located on the vertices. In the second stage, they start exploring the area by moving between vertices of the grid. Furthermore, it is assumed that the communication range of the robots is limited, and the algorithm is based on the information of the nearest neighbours of the robots. Moreover, we apply a new mapping method employed by robots during the search operation. A mathematically rigorous proof of convergence with probability 1 of the algorithm is given. Moreover, our algorithm is implemented and simulated using a simulator of the real robots and environment and also tested via experiments with Adept Pioneer 3DX wheeled mobile robots.

Use of multi-robot systems has many advantages over single robot systems in various applications. However, it comes with its own complexity and challenges. In this report, we try to improve the performance of existing approaches for search operations in multi-robot context. We propose three novel algorithms that are using a triangular grid pattern, i.e., robots certainly go through the vertices of a triangular grid during the search procedure. The main advantage of using a triangular grid pattern is that it is asymptotically optimal in terms of the minimum number of robots required for the complete coverage of an arbitrary bounded area. Therefore, using the vertices of this triangular grid coverage guarantees complete search of a region as well as shorter searching time. We use a new topological map which is made and shared by robots during the search operation. We consider an area that is unknown to the robots a priori with an arbitrary shape, containing some obstacles. Unlike many current heuristic algorithms, we give mathematically rigorous proofs of convergence with probability 1 of the algorithms. The computer simulation results for the proposed algorithms are presented using a simulator of real robots and environment. We evaluate the performance of the algorithms via experiments with real Pioneer 3DX mobile robots. We compare the performance of our own algorithms with three existing algorithms from other researchers. The results demonstrate the merits of our proposed solution.A further study on formation building with obstacle avoidance for a team of mobile robots is presented in this report. We propose a robust decentralized formation building with obstacle avoidance algorithm for a group of mobile robots to move in a defined geometric configuration. Furthermore, we consider a more complicated formation problem with a group of anonymous robots; these robots are not aware of their position in the final configuration and need to reach a consensus during the formation process. We propose a randomized algorithm for the anonymous robots that achieves the convergence to a desired configuration with probability 1. We also propose a novel obstacle avoidance rule, used in the formation building algorithm. A mathematically rigorous proof of the proposed algorithm is given. The performance and applicability of the proposed algorithm are confirmed by the computer simulation results.

This paper considers the problem of detecting mobile targets moving in a 3D space by a mobile robotic sensor network. We propose a bio-inspired random search mechanism supplemented with a grid based distribution strategy for search in bounded 3D areas. Using this algorithm, the mobile robots do the search task by randomly moving to the vertices of a common 3D covering grid from any initial position. The proposed algorithm uses some simple consensus rules for building a common covering grid, also it uses a random walk search pattern drawn by a Levy flight probability distribution to do the search task. Performance of the proposed algorithm is evaluated by simulations and comparison to the Levy walk random search method. Also, we give mathematically rigorous proof of convergence with probability 1 of the proposed algorithm.