Skip navigation.

Search Methodologies for Node Recovery in Robotic Swarms

Publication Type:

Conference Paper


19th Mediterranean Conference on Control and Automation (MED'11) (2011)


Keywords-Heuristic methods; Unmanned Systems Network; Communication Coverage


Groups of autonomous robots become increasingly useful
as the mission complexity they can handle increases.
However, in a mobile ad hoc network, there are continually
communication failures due to changing environmental
conditions and of course hardware problems, both temporary
and permanent. For this work, we envision a
heterogeneous robotic swarm with both “general” nodes
that perform mission tasks, and “support” nodes that help
maintain the connectivity of the communication network.
At any given time, there are likely to be multiple network
link failures, so the placement of support nodes becomes
an optimization problem: where will the support nodes
be most effective. In a realistic scenario, this optimization
problem would be solved constantly as robots move around
and the network topology changes, so the technique
used must be both efficient, and close to optimal. This
paper describes the study of three optimization methods
– particle swarm optimization, hill climbing, and tabu
search to solve this problem. We find that particle swarm
optimization provides the best solutions, but takes a little
bit more time to execute than tabu search or hill climbing.