The purpose of this project is to design, implement and evaluate bee-inspired algorithm for MUTA problem which is inspired by bee colony. The main motivations behind this project is to increase the efficiency of search and rescue (SAR) missions by efficient allocation of different tasks among multiple UAVs participating in the mission. The end aim is to find more victims and rescue them given the strict time frame of SAR missions.
This project is of multidisciplinary nature combing three fields: first, unmanned aerial vehicles (UAVs) which are “aircrafts with no pilot on board”. Second, the task allocation problem which is NP-hard. This problem focuses on the efficient distribution of tasks among multiple agents. Finally, the bio-inspired algorithms in which biological natural systems are mimicked in engineering systems to find efficient solution for complex problems, such as the task allocation dilemma.
There are already some available approaches for task allocation in multi-UAVs /multi-robot missions, such as auction based algorithms and bio-inspired algorithms including fish swarm algorithms, bee-inspired algorithms, locust- inspired algorithms and ant colony algorithms. Auction-based algorithms suffer from extensive computation and communication overheads. Hence, in this project we followed the bio-inspired approach due to its advantages by offering better computation and communication techniques. The design of the proposed algorithm system (BMUTA) and its evaluation framework were presented in details to provide a clear plan for the incoming phases.