Abstract:
In this paper, we describe an accurate method for localization of a mobile robot using bluetooth. We introduce novel approaches for obtaining distance estimates and trila...Show MoreMetadata
Abstract:
In this paper, we describe an accurate method for localization of a mobile robot using bluetooth. We introduce novel approaches for obtaining distance estimates and trilateration that overcome the hitherto known limitations of using Bluetooth for localization. Our approach is reliable and has the potential of being scaled to multi-agent scenarios. The proposed approach was tested on a mobile robot, and we present the experimental results. The error obtained was 0.427 ± 0.229 m, which proves the accuracy of our method.
Date of Conference: 03-07 May 2010
Date Added to IEEE Xplore: 15 July 2010
ISBN Information:
Print ISSN: 1050-4729
Keywords assist with retrieval of results and provide a means to discovering other relevant content. Learn more.
- IEEE Keywords
- Index Terms
- Indoor Environments ,
- Mobile Robot ,
- Robot Localization ,
- Localization In Indoor Environments ,
- Vector Control ,
- Measurement Model ,
- System Of Equations ,
- Power Level ,
- Global Positioning System ,
- Kalman Filter ,
- Power Control ,
- Posterior Density ,
- Dirac Delta ,
- Pseudo-inverse ,
- Particle Filter ,
- Measurement Vector ,
- Odometry ,
- Position Of The Robot ,
- Robot State ,
- Received Signal Strength Indicator ,
- Orientation Of The Robot ,
- Bayesian Filtering ,
- Negligible Weight ,
- Robot Pose ,
- Research Methods ,
- Wireless Technologies ,
- Static Position
Contents Keywords assist with retrieval of results and provide a means to discovering other relevant content. Learn more.
- IEEE Keywords
- Index Terms
- Indoor Environments ,
- Mobile Robot ,
- Robot Localization ,
- Localization In Indoor Environments ,
- Vector Control ,
- Measurement Model ,
- System Of Equations ,
- Power Level ,
- Global Positioning System ,
- Kalman Filter ,
- Power Control ,
- Posterior Density ,
- Dirac Delta ,
- Pseudo-inverse ,
- Particle Filter ,
- Measurement Vector ,
- Odometry ,
- Position Of The Robot ,
- Robot State ,
- Received Signal Strength Indicator ,
- Orientation Of The Robot ,
- Bayesian Filtering ,
- Negligible Weight ,
- Robot Pose ,
- Research Methods ,
- Wireless Technologies ,
- Static Position
