An Event-Triggered Distributed Continuous-Time Optimization Approach

In this paper, we design an event-triggered distributed continuous-time optimization approach. The proposed approach can be implemented independently by each robot and has two main characteristics. One is that each robot can deal with its local cost function such that the minimum of the sum of all the local cost functions can be found. The other is that, due to using the event-triggered communication mechanism, resource consumption of chips are saved by reducing the communication frequencies and the updating times of control inputs before the consensus is arrived. Moreover, based on Lyapunov theory, the stability conditions of multi-robot systems with the proposed approach are given. Finally, the effectiveness of the proposed approach is illustrated through experimental results.