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Thesis

Multi-agent exploration of indoor environments under limited communication constraints

Abstract:

This thesis considers cooperation strategies for teams of agents autonomously exploring an unknown indoor environment under limited communication constraints. The primary application considered is Urban Search-and-Rescue, although other applications are possible, such as surveying hazardous areas. We focus on developing cooperation strategies that enable periodic communication between the exploring agents and the base station (human operators). Such strategies involve an inherent trade-off between allocating team resources towards facilitating communication and increasing the speed of exploration.

We propose two classes of approaches to address this problem: using opportunistic rendezvous to guide the team behaviour, and explicitly arranging rendezvous between agents. In the opportunistic approach, the allocation of team resources between exploration and communication can be indicated with a single numerical parameter between 0 and 1 -- the return ratio -- which leads to complex emergent cooperative behaviour. We show that in some operating environments agents can benefit from explicitly arranging rendezvous. We propose a novel definition of a rendezvous location as a tuple of points and show how such locations can be generated so that the topology of the environment and the communication ranges of agents can be exploited. We show how such rendezvous locations can be used to both improve the speed of exploration and to improve team connectivity by allowing relays to contribute to the overall exploration.

We evaluate these approaches extensively in simulation and discuss their applicability in search-and-rescue scenarios.

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Division:
MPLS
Department:
Computer Science
Department:
Computer Science
Role:
Author

Contributors

Department:
Computer Science
Role:
Supervisor
Department:
Politecnico di Milano
Role:
Examiner
Department:
Computer Science
Role:
Examiner


Type of award:
DPhil
Level of award:
Doctoral
Awarding institution:
University of Oxford


Language:
English
Keywords:
Subjects:
UUID:
uuid:b337a9a7-91c7-451c-b32f-b1cd05ef983d
Deposit date:
2017-01-31

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