Cooperative localization by using knowledge of self-organized regularity

Authors:
Masao Kubo;Takashi Matsubara;Satoshi Shimizu;Hiroshi Sato
Affiliations:
Computer Science, National Defense Academy of Japan, Yokosuka, Japan;Computer Science, National Defense Academy of Japan, Yokosuka, Japan;Computer Science, National Defense Academy of Japan, Yokosuka, Japan;Computer Science, National Defense Academy of Japan, Yokosuka, Japan
Venue:
Artificial Life and Robotics
Year:
2010

Citing 3
Cited 0

Distributed particle filters for sensor networks

Proceedings of the 3rd international symposium on Information processing in sensor networks
Probabilistic Robotics (Intelligent Robotics and Autonomous Agents)

Probabilistic Robotics (Intelligent Robotics and Autonomous Agents)
Resampling algorithms and architectures for distributed particle filters

IEEE Transactions on Signal Processing

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this article, a new localization approach for a team of robots that use the emergent properties of their formation is proposed. Synchronized behavior sometimes generates spin-off effects that include geometric patterns. The question then arises as to whether it is possible to use these patterns for something important for robots. In this article, Takayama's control strategy, which is a target enclosure formation, is discussed. A simple and useful expansion of Monte Carlo localization by the emergent pattern is proposed. The proposed algorithms are confirmed through a series of computer simulations.