Paper Info
Title
Aggregation in robot swarms using odometry
Abstract
Aggregation is a useful building block behaviour that can allow a swarm of robots to interact with each other or a user more easily. Previous work on swarm robot aggregation has assumed that the capabilities of individual robots are quite limited. We test whether incorporating odometry as an additional capability is helpful and make the argument that odometry is both realizable and biologically plausible. We propose an algorithm called ODOCLUST which takes inspiration from the BEECLUST algorithm but uses a continuously active odometry-based homing process to achieve more tightly packed robot aggregates more quickly than BEECLUST. Initial results in simulation suggest that high-fidelity odometry is not required in order to see these gains.
Year
DOI
Venue
2016
10.1007/s10015-016-0333-2
Artificial Life and Robotics
Keywords
DocType
Volume
Swarm robotics, Aggregation, Odometry
Journal
21
Issue
ISSN
Citations 
4
1433-5298
0
PageRank 
References 
Authors
0.34
6
1
Name
Order
Citations
PageRank
Andrew Vardy114012.65