scholarly journals Mutual Localization of Multiple Sensor Node Robots

2011 ◽  
Vol 15 (9) ◽  
pp. 1269-1276 ◽  
Author(s):  
Keitaro Naruse ◽  
◽  
Shigekazu Fukui ◽  
Jie Luo
Keyword(s):  
Kalman Filter ◽  
Mobile Robots ◽  
Extended Kalman Filter ◽  
Sensor Node ◽  
Localization Error ◽  
Localization Problem ◽  
Position Information ◽  
Omnidirectional Camera ◽  
Amount Of Information ◽  
Multiple Sensor

The objective of this paper is to develop a localization systemof cooperativemultiple mobile robots, in which each robot is assumed to observe a set of known landmarks and equipped with an omnidirectional camera. In this paper, it is assumed that a robot can detect other robots by using the omnidirectional camera, share its estimated position with others, and utilize shared positions for its localization. In other words, each robot can be viewed as an additional mobile landmark to a set of stationary landmarks. A foremost concern is how well this system performs localization under a limited amount of information. This paper presents an investigation of self localization error of each robot in a group using Extended Kalman Filter to solve the localization problem with the insufficient landmarks and inaccurate position information.

A Localization Algorithm for Autonomous Mobile Robots via a Fuzzy Tuned Extended Kalman Filter

2010 ◽  
Vol 24 (1-2) ◽  
pp. 179-206 ◽  
Author(s):  
Y. L. Ip ◽  
A. B. Rad ◽  
Y. K. Wong ◽  
Y. Liu ◽  
X. M. Ren
Keyword(s):  
Kalman Filter ◽  
Mobile Robots ◽  
Extended Kalman Filter ◽  
Autonomous Mobile Robots ◽  
Localization Algorithm

Improved GNSS Localization with the Use of DOP Parameter

2014 ◽  
Vol 611 ◽  
pp. 450-466 ◽  
Author(s):  
František Duchoň ◽  
Jaroslav Hanzel ◽  
Andrej Babinec ◽  
Jozef Rodina ◽  
Peter Paszto ◽  
...  
Keyword(s):  
Kalman Filter ◽  
Mobile Robots ◽  
Reference Frame ◽  
Small Scale ◽  
Localization Error ◽  
Localization Accuracy ◽  
Gnss Receiver ◽  
Gps Localization

This paper presents the approach to improve localization based on GNSS. The principles of the GPS localization and impact of the DOP parameter on localization error are mathematically analyzed. The algorithm based on the use of DOP parameter and Kalman filter for the improvement of the localization accuracy suitable for small scale outdoor mobile robots and other outdoor applications is proposed. The applicability of the proposed methodology was verified by performed experiments with two common cheap miniature GPS modules and accurate high-end GNSS receiver used as a reference frame for the measurements. The obtained results affirmed the improvement of the localization accuracy.

Odometry in Cooperative Multi-Mobile Robots

1999 ◽  
Vol 11 (5) ◽  
pp. 411-416
Author(s):  
Masafumi Hashimoto ◽  
◽  
Takanori Kurazumi ◽  
Fuminori Oba ◽  
Keyword(s):  
Kalman Filter ◽  
Mobile Robots ◽  
Extended Kalman Filter ◽  
Position Sensor ◽  
Location Errors ◽  
Exchange Information ◽  
Sensor Information

We propose odometry in cooperative multi-mobile robots by integrating conventional odometry and interrobot position sensor information. In our odometry, each robot is considered a moving landmark with imprecise location. Robots in the group locally estimate their own absolute positions based on conventional odometry and find the relative positions of each other using interrobot position sensors. They communicate and exchange information on local estimates and relative positions. The information is integrated decentralized based on the extended Kalman filter and robots improve their absolute positions. Simulation and experiments show that our odometry eliminates large robot location errors found in conventional odometry.

Kalman Filtering-Aided Optical Localization of Mobile Robots: System Design and Experimental Validation

2017 ◽  
Author(s):  
Jason N. Greenberg ◽  
Xiaobo Tan
Keyword(s):  
Kalman Filter ◽  
Mobile Robots ◽  
Kalman Filtering ◽  
Experimental Validation ◽  
Line Of Sight ◽  
Localization Error ◽  
Two Dimensional ◽  
Prior Work ◽  
Localization Performance ◽  
Mobile Base

Localization of mobile robots in GPS-denied envrionments (e.g., underwater) is of great importance to achieving navigation and other missions for these robots. In our prior work a concept of Simultaneous Localization And Communication (SLAC) was proposed, where the line of sight (LOS) requirement in LED-based communication is exploited to extract the relative bearing of the two communicating parties for localization purposes. The concept further involves the use of Kalman filtering for prediction of the mobile robot’s position, to reduce the overhead in establishing LOS. In this work the design of such a SLAC system is presented and experimentally evaluated in a two-dimensional setting, where a mobile robot localizes itself through wireless LED links with two stationary base nodes. Experimental results are presented to demonstrate the feasibility of the proposed approach and the important role the Kalman filter plays in reducing the localization error. The effect of the distance between the base nodes on the localization performance is further studied, which bears implications in future SLAC systems where mobile base nodes can be reconfigured adaptively to maximize the localization performance.

Localization of Mobile Robots Using an Extended Kalman Filter in a LEGO NXT

2012 ◽  
Vol 55 (1) ◽  
pp. 135-144 ◽  
Author(s):  
Miguel Pinto ◽  
António Paulo Moreira ◽  
Aníbal Matos
Keyword(s):  
Kalman Filter ◽  
Mobile Robots ◽  
Extended Kalman Filter
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