CARE: A Collision-Aware Mobile Robot Navigation in Grid Environment using Improved Breadth First Search

Localization strategies for autonomous mobile robots: A review

This paper brings an efficient low complexity path-finding algorithm for autonomous mobile robot in a grid-based environment. Research is carried out by using a hybrid approach which combines the greedy strategy with proposed improving BFS (I-BFS) algorithm. A robot adopts localization strategy based on the environment in which it is employed. The radio frequency identification (RFID)-based localization is quite challenging and is adopted by various authors for localizing robots in indoor environment. The proposed navigation algorithm utilizes RFID technique for positioning the mobile robot which is a substitute for existing vision-based approaches. The added features like both obstacle detection and avoidance are the most promising factor of the proposed methodology. The methodology generated an optimal shortest path in an unknown grid-structured environment through repeated exploration. In this paper, both computationally effective and cost-efficient solution is made for an alternative to several mobile robot navigation algorithms. The navigation algorithm presented here can be used for autonomous vehicular robot employed in different environments like buildings, hospitals, shopping malls, etc., for effective path planning. The simulation result establishes the efficiency of the proposed navigation algorithm. 

Intelligent Path Planning with Improved BFS (I-BFS) Strategy for Mobile Robot in RFID Equipped Unknown Environment

Purpose of research. The research presented in this article is aimed at improving the speed of finding a path for the movement route of robots. The scientific novelty is the obtained correlation of time and field size.Methods. To find the path in the maze, the depth-first search and breadth-first search algorithms were used, the basis of which is the cyclic processing of adjacent previously unvisited graph vertices. Performance is estimated in terms of the speed of program code execution on prepared samples. Scientific novelty was obtained by studying the influence of map sizes on the performance of depth-first and breadth-first search algorithms.Results. A software implementation of breadth-first and depth-first search algorithms has been developed. The article provides a more detailed description of the breadth-first search algorithm in the form of pseudo and program codes, which are based on the while loop, where the queue of checked graph vertices is processed. Based on the evaluation of the speed of the found path, it was concluded that the breadth-first search is not the fastest. Based on the assessment of the influence of various factors on the speed of the algorithm, it was concluded that an increase in the size of the field, a decrease in the number of obstacles and a distance between the starting and final points increases the execution time of the algorithm.Conclusion. The breadth-first search algorithm and its software implementation were presented. In the course of experimental studies, it was found that this algorithm is not the fastest in time, but in all tests, it found the shortest path. The correlation ta = f(w, h) was also obtained for the prepared samples of the desired field, which is expressed as the dependence of the algorithm execution time on the length and width of the field. And we can conclude that it is applicable for finding the movement path of robots, since it always finds the shortest path.

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Research of the Properties of the Breadth-First Search Algorithm for Finding the Movement Route of Robots

Path-finding is a fundamental problem, which involves for solving a planning problem seeking optimal paths from start state to a goal state. This review paper focused on usage of Radio Frequency Identification (RFID) technology in path-finding and navigation for an autonomous mobile robot. The RFID tags (IC tags) are used for the purpose of tracing the current co-ordinate/location of the Robot. Various searching algorithms are analyzed for the purpose towards navigation of mobile robot. Different soft-computing techniques like Genetic Algorithm, Neural Network, and Fuzzy Logic are considered. This research also focused on some hybrid algorithm for path-finding and navigation of mobile robot. Different methods like cellular automata, Network Simplex Method, Complete Coverage Navigation etc. are also studied.

Hrudya Kumar Tripathy

Papers

Analysis on Intelligent Based Navigation and Path Finding of Autonomous Mobile Robot