<p> In dense cluttered environments, autonomous physical agents will face many challenges including limited routes, obstructed sensors, and limited communication. Equipping the agents with inter-agent communication alleviates some of the issues, but providing a mechanism for forming groups allows the agents to work together efficiently by avoiding congestion in tight areas and providing redundancy to accomplish a task. This thesis presents a framework for decentralized collaborative group formations and a framework for augmenting that with a more strategic centralized approach. This thesis will investigate a strategy for the formation of hierarchical ad-hoc groups that provide a simple interface for joining and splitting groups. After formation these groups will use peer to peer algorithms to share sensor data and perform distributed task allocation within the group. The groups can either be controlled by a static base-station or use a decentralized framework if communication to the base-station is lost. When communication is restored, the peer to peer algorithms will be used to spread the data to as many agents as possible to avoid data loss. A radio propagation model is also presented to simulate communication in indoor and simulated environments, as well as estimated propagation for use in path planning. This framework will also allow the agent's high level decision making to modify its role depending on group consensus. </p>
| Identifer | oai:union.ndltd.org:PROQUEST/oai:pqdtoai.proquest.com:3734570 |
| Date | 02 December 2015 |
| Creators | Biddlestone, Scott |
| Publisher | The Ohio State University |
| Source Sets | ProQuest.com |
| Language | English |
| Detected Language | English |
| Type | thesis |
Page generated in 0.0017 seconds