Mission control - combined solutions for source seeking and level curve tracking in a time-varying field

In this paper we propose a novel mission control strategy for a group of agents to locate an unknown source, represented as maximum of a scalar field, and to track a specified level curve. We propose a distributed control scheme based on hierarchy formation and reduced topology. Without prior knowledge of the field, the agents, equipped with local sensors, navigate in ℝ
^p
using an estimated gradient method and their neighbors' shared measurements. The contributions of this paper are twofold. First, we propose a finite iteration process for reaching a discrete consensus between all agents for switching from one task to the next. Each group of agents determines their current task according to the status of the other groups in the network. Second, a 4-tasks algorithm is proposed for exploring a time-varying, noisy field. Simulations for a group of 32 agents are shown, illustrating the algorithm robustness to a time-varying field with noise corrupted measurements.