Name
Abstract | ||
|---|---|---|
Consensus algorithms allowmultiple robots to achieve agreement on estimates of variables in a distributed manner, hereby coordinating the robots as a team, and enabling applications such as formation control and cooperative area coverage. These algorithms achieve agreement by relying only on local, nearest-neighbor communication. The problem with distributed consensus, however, is that a single malicious or faulty robot can control and manipulate the whole network. The objective of this paper is to propose a formation topology that is resilient to one malicious node, and that satisfies two important properties for distributed systems: (i) it can be constructed incrementally by adding one node at a time in such a way that the conditions for attachment can be computed locally, and (ii) its robustness can be verified through a distributed method by using only neighborhood-based information. Our topology is characterized by triangular robust graphs, consists of a modular structure, is fully scalable, and is well suited for applications of large-scale networks. We describe how our proposed topology can be used to deploy networks of robots. Results show how triangular robust networks guarantee asymptotic consensus in the face of a malicious agent. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1007/978-3-319-73008-0_11 | Springer Proceedings in Advanced Robotics |
Field | DocType | Volume |
Consensus,Consensus algorithm,Graph,Computer science,Robustness (computer science),Robot,Modular structure,Scalability,Area coverage,Distributed computing | Conference | 6 |
ISSN | Citations | PageRank |
2511-1256 | 1 | 0.35 |
References | Authors | |
0 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| David Saldana | 1 | 32 | 9.61 |
| Amanda Prorok | 2 | 97 | 9.17 |
| Mario Fernando Montenegro Campos | 3 | 557 | 51.60 |
| Vijay Kumar | 4 | 7086 | 693.29 |