Decentralized dynamic task planning for heterogeneous robotic networks

In this paper, we propose a decentralized model and control framework for the assignment and execution of tasks, i.e. the dynamic task planning, for a network of heterogeneous robots. The proposed modeling framework allows the design of missions, defined as sets of tasks, in order to achieve global objectives regardless of the actual characteristics of the robotic network. The concept of skills, defined by the mission designer and considered as constraints for the mission execution, is exploited to distribute tasks across the robotic network. In addition, we develop a decentralized control algorithm, based on the concept of skills for decoupling the mission design from its deployment, which combines task assignment and execution through a consensus-based approach. Finally, conditions upon which the proposed decentralized formulation is equivalent to a centralized one are discussed. Experimental results are provided to validate the effectiveness of the proposed framework in a real-world scenario.