Cooperative Decentralized Continuous Filter with Bearing to Unknown Features and Relative Bearing and Range Measurements between Robotic Agents

Neha Satak, Kevin Brink

Abstract:	A cooperative estimation framework is developed allowing robotic agents to share inter-agent and environmental measurement information which improves the estimation accuracy of the individual cooperating agents. This paper describes an extension of traditional monocular simultaneous localization and mapping (SLAM) enabling a distributed, networked approach. Noisy odometry measurements are available for each agent, and monocular cameras provide bearing measurements to unknown features observed in the environment. It is assumed that relative range and bearing measurements between agents are sometimes available and that agents can also communicate recent bearing measurements to the unknown features.
Published in:	Proceedings of the ION 2015 Pacific PNT Meeting April 20 - 23, 2015 Marriott Waikiki Beach Resort & Spa Honolulu, Hawaii
Pages:	350 - 354
Cite this article:	Satak, Neha, Brink, Kevin, "Cooperative Decentralized Continuous Filter with Bearing to Unknown Features and Relative Bearing and Range Measurements between Robotic Agents," Proceedings of the ION 2015 Pacific PNT Meeting, Honolulu, Hawaii, April 2015, pp. 350-354.
Full Paper:	ION Members/Non-Members: 1 Download Credit Sign In