Professor of School of Engineering, Design and Built Environment, Western Sydney University, Australia. His research interests cover Industry 4.0, Additive Manufacturing, Advanced Engineering Materials and Structures (Metals and Composites), Multi-scale Modelling of Materials and Structures, Metal Forming and Metal Surface Treatment.
Abstract— Several applications have been implemented since the advent of mobile robots. Such applications include, but are not limited to, performing search and rescue missions and optimizing the material handling process in automated warehouses. This high interest in the field of cooperative Multi-Robot Systems is due to their robustness and flexibility, in addition to their high performance and affordability. In this study, an algorithm for the Multi-Robot Task Allocation problem has been developed to incubate the two well-known approaches for system architectures which are centralized and decentralized approaches. The algorithm utilizes the advantages of both approaches in a Multi-level structure and uses an economic, Market-Based Approach, to solve the problem. Several attributes have been considered and encapsulated in the robots and tasks such as the energy levels of the robots, which play an important role in solving the task allocation problem. The algorithm has been tested on three different known environments with different complexities and sizes. Several scenarios have been tested by varying the number of robots and tasks. Results show high performance of the algorithm and its applicability in solving the Multi-Robot Task Allocation Problem.
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