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Experimental Implementation of Multi-Agent Distributed Optimization Algorithms With Shortest Distance to Convex Regions

Creative Commons 'BY' version 4.0 license

The focus of this thesis is on the multi-agent rendezvous problem where the rendezvous location has the total squared shortest distance to certain regions. Three algorithms

are experimentally implemented under an undirected communication topology. Simulation plots and experimental results are demonstrated on a multi-robot platform to validate the proposed algorithms. First, an implementation of the distributed subgradient shortest-distance rendezvous algorithm is implemented. Second, an alternative distributed shortest-distance rendezvous algorithm which introduces a kind of diminishing step sizes is validated. Third, an algorithm with employment of two internal states of the dynamic averaging estimator is implemented. This thesis illustrates the three algorithms by presenting simulation plots in Matlab, robots’ moving trajectories in the multi-robot platform, and plots of the shortest distance performance function.

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