Optimized Dynamic Task Allocation and Priority Assignments in an Immunized Autonomous Multi-Robot Search and Rescue Operation
This paper discusses the optimization of the cost function for task allocation and conflict resolution in robots in immune-based cooperative multi-robot search and rescue missions. In this research, robots respond to an emergency situation such as a bomb blast or an earthquake, approach the site, and assemble a structure out of parts collected from the debris in order to evacuate the injured people. A genetic algorithm is used to optimize the cost function that determines the most suitable robot that can transport or help another robot to transport the part to an assembly location in order to build a structure. Further, a priority assignment method is suggested for different parts based on their order dependencies. Decision conflicts among the robots are also discussed and solutions to resolve them are provided. The developed scheme is verified through simulation of immune-based multi-robot cooperation.
artificial immune system cooperative transport cost optimization multi-robot systems