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Precise Localization for Autonomous Mobile Robot Using Passive RFID

This research proposes an efficient method for precise localization and navigation of mobile robots in indoor environments using passive RFID technology. By utilizing trigonometric functions and Cartesian coordinates from RFID tags, the robot achieves more accurate positioning and trajectory planning without the need for external sensors. The system overcomes uncertainties and offers a cost-effective solution for navigation. Experimental results validate the effectiveness of the proposed algorithm in enhancing robot localization and orientation accuracy. No extra sensors are required, making it a practical and reliable option for autonomous robot navigation.

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Precise Localization for Autonomous Mobile Robot Using Passive RFID

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  1. Autonomous mobile robot navigation using passive RFID in indoor environment Presented for:CPS Lab-ASUBy: RamtinKermani IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, VOL. 56, JULY 2009Sunhong Park and Shuji Hashimoto

  2. Goal • The paper proposes an efficient method for localization and pose estimation for mobile robot navigation using passive radio-frequency identification (RFID). • Realize Location and Pose using the relation Between previous and current tag • Problem: Uncertainty  Error, always there! • Prev. Solutions: Using External Sensors • This Paper uses trigonometric functions and the IC tags’ Cartesian coordinates in a regular gridlikepattern to obtain the “more precise” location and pose. • Results in a more efficient tragectory.

  3. How RFID works? • Radio Frequency Identification • The system includes: • RFID Reader (Interrogator) • RFID Tag (Transponder) • Passive Tags • Semi-Pasive Tags • Active Tags

  4. RFID Components Parallax TTL RFID Reader Parallax USB RFID Reader

  5. Robot Localization and Navigation • “Where am I ?”, • “Where am I going ?”, and • “How do I go there?” • Main problem with Robot navigation: • The estimation error accumulates over time since no external reference signals are employed for correction  Using External Sensors (cameras, laser range finders, sonar, GPS, etc.) • BUT! The landmarks are not always observable due to the influence of ambient light and shielding obstacles

  6. Navigation Using RFID systems • Error prone due to the nature of the Antenna • Binary Presence Detection • Weak signal reception and measurement should be considered. • Should deal with uncertainty • Should be able to read multiple tags • Should not need a lot of tags for a simple application  Not economical

  7. In this paper, a method for estimating both location and pose information of a mobile robot using only passive radio-frequency identification (RFID) is proposed.

  8. The Robot: UBIRO • UBIRO: UBIquitousRObot • UBIRO consists of three main parts: • The PC for control, • The RFID system for obtaining the location information of robot, • The mobile base for navigation

  9. Uncertainty of robot location.

  10. Proposed method of localization Xcurrent=r cosƟ’+ x1 (7) Ycurrent =r sin Ɵ’ + y1 (8) - The θ is given by the accumulation of the rotation angle of the robot. - The robot repeats a forward and rotation movement autonomously until it reaches the goal

  11. Overall concept of proposed method

  12. Procedure of Navigation

  13. Calculating the rotation angle for navigation to the goal:

  14. Experiments • To evaluate the validity of localization and pose estimation using the proposed algorithm for mobile robot navigation, we conducted experiments under three kinds of conditions. • Condition 1, the initial pose of the mobile robot was 0◦, i.e., the positive Y -axis. • Condition 2 was 90◦. • Finally, condition 3 was −90◦.

  15. Results

  16. Conclusion • we have described an efficient method that considers uncertainty for estimating the location and orientation of a mobile robot using a passive RFID system. • precisely acquire the location and orientation of the robot based on information of the placement of the IC tags. • No extra Sensors Required • Just one RFID Reader on the Robot • More precise Localization and Navigation compared to conventional methods proposed by other researchers.

  17. Future Work • In the near future, we aim at improving the navigation algorithm to identify the IC tags which will allow the mobile robot to navigate through more dynamic environments with obstacles. We

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