Time-Inverted Kuramoto Model Meets Lissajous Curves
Multi-Robot Persistent Monitoring and Target Detection
M. Boldrer (TU Delft - Learning & Autonomous Control)
L. Lyons (TU Delft - Learning & Autonomous Control)
Luigi Palopoli (Università degli Studi di Trento)
Daniele Fontanelli (Università degli Studi di Trento)
Laura Ferranti (TU Delft - Learning & Autonomous Control)
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Abstract
This letter proposes a distributed strategy to achieve both persistent monitoring and target detection in a rectangular and obstacle-free environment. Each robot has to repeatedly follow a smooth trajectory and avoid collisions with other robots. To achieve this goal, we rely on the time-inverted Kuramoto dynamics and the use of Lissajous curves. We analyze the resiliency of the system to perturbations or temporary failures, and we validate our approach through both simulations and experiments on real robotic platforms. In the letter, we adopt Model Predictive Contouring Control as a low level controller to minimize the tracking error while accounting for the robots' dynamical constraints and the control inputs saturation. The results obtained in the experiments are in accordance with the simulations.