Task allocation in multi-robot system using resource sharing with dynamic threshold approach

Task allocation is a fundamental requirement for multi-robot systems working in dynamic environments. An efficient task allocation algorithm allows the robots to adjust their behavior in response to environmental changes such as fault occurrences, or other robots' actions to increase overall system performance. To address these challenges, this paper presents a Task Allocation technique based on a threshold level which is an accumulative value aggregated by a centralized unit using the Task-Robot ratio and the number of the available resource in the system. The threshold level serves as a reference for task acceptance and the task acceptance occurs despite resource shortage. The deficient resources for the accepted task are acquired through an auction process using objective minimization. Despite resource shortage, task acceptance occurs. The threshold approach and the objective minimization in the auction process reduce the overall completion time and increase the system's resource utilization up to 96%, which is demonstrated theoretically and validated through simulations and real experimentation.