An optimized task allocation for multi robot systems using soft computing techniques

Modern researches in technology and industrial developments have been prominent to the anxiety of multirobot Systems (MRS) performing more composite task. As MRS systems consist of several individual robots, it must be decided whether those robots must all be identical or whether they may differ from each other. This paper inspects solution of the allocation problem in MRS that is for assignment of tasks to the robots. Tasks have to choose from a list of space and time basis requirement, indicating their availability in advance. In this problem there is m robots and n task, where each robot is assigned to a single task so, as to minimize the allocation cost. There are m×n ways of solutions in which to search for the globally optimized one. The objective is to find the assignment such as to maximize the appeal of the allocation and to minimize the cost of the allocation. Results are given which show that the Simulated Annealing (SA) produces better solutions than the Genetic Algorithm (GA) problem. The SA approach is used to determine the most excellent obtainable combination of resources for Robot-task allocation.