Multi-robot task allocation clustering based on game theory

Game Theory Based Task Planning in Multi Robot Systems

In the paper we discuss a problem of planning and coordination in a multi robot system. We consider a team of robots that performs a global task in a humanmade workspace of complex structure. A hybrid architecture of the team motion control system is considered. The system can be split into two layers: the planner module and the behavior based collision free motion controller, that is designed ...

Swarm-Intelligence-based Multi-Robot Task Allocation

Multi-Robot Task Allocation (MRTA) in an unknown environments is a core problem in automated systems. To complete all tasks in the environment, three distinct steps are needed to be performed: exploration, task allocation, and task execution. We propose a hierarchical algorithm based on swarm intelligence to perform these three steps concurrently in order to improve the overall system performan...

Sensor network-based multi-robot task allocation

We present DINTA, Distributed In-network Task Allocation a novel paradigm for multi-robot task allocation (MRTA) where tasks are allocated implicitly to robots by a pre-deployed, static sensor network. Experimental results with a simulated alarm scenario show that our approach is able to compute solutions to the MRTA problem in a distributed fashion. We compared our approach to a strategy where...

Transmission cost allocation based on cooperative game theory

Multi-robot Task Allocation Based on Ant Colony Algorithm

With the development of information technology, the capability and application fields of robots become wider. In order to complete a complex task, the cooperation and coordination of robots are needed to be adopted. As the main problem of the multi-robot systems, multi-robot task allocation (MRTA) reflects the organization form and operation mechanism of the robots system. The cooperation and a...