An Improved Position Estimation Algorithm for Localization of Mobile Robots by Sonars

2005 ◽  
Author(s):  
Joe W. Yeol
Keyword(s):  
Mobile Robots ◽  
Estimation Algorithm ◽  
Position Estimation

Accurate 3D Localization Using RGB-TOF Camera and IMU for Industrial Mobile Robots

Robotica ◽  
2021 ◽  
pp. 1-18
Author(s):  
Majid Yekkehfallah ◽  
Ming Yang ◽  
Zhiao Cai ◽  
Liang Li ◽  
Chuanxiang Wang
Keyword(s):  
Mobile Robots ◽  
Inertial Measurement Unit ◽  
Indoor Environment ◽  
State Of The Art ◽  
Low Cost ◽  
Estimation Algorithm ◽  
Measurement Unit ◽  
3D Localization ◽  
Fast Motion ◽  
Tof Camera

SUMMARY Localization based on visual natural landmarks is one of the state-of-the-art localization methods for automated vehicles that is, however, limited in fast motion and low-texture environments, which can lead to failure. This paper proposes an approach to solve these limitations with an extended Kalman filter (EKF) based on a state estimation algorithm that fuses information from a low-cost MEMS Inertial Measurement Unit and a Time-of-Flight camera. We demonstrate our results in an indoor environment. We show that the proposed approach does not require any global reflective landmark for localization and is fast, accurate, and easy to use with mobile robots.

scholarly journals GPS Receiver Position Augmentation Using Correntropy Kalman Filter in Low Latitude Terrain

2022 ◽  
Author(s):  
Sirish Kumar Pagoti ◽  
Bala Sai Srilatha Indira Dutt Vemuri ◽  
Ganesh Laveti
Keyword(s):  
Kalman Filter ◽  
Indian Subcontinent ◽  
Estimation Algorithm ◽  
Position Estimation ◽  
Gps Receiver ◽  
Dual Frequency ◽  
Low Latitude ◽  
Position Accuracy ◽  
Aircraft Landing ◽  
Gps Accuracy

If any Global Positioning System (GPS) receiver is operated in low latitude regions or urban canyons, the visibility further reduces. These system constraints lead to many challenges in providing precise GPS position accuracy over the Indian subcontinent. As a result, the standalone GPS accuracy does not meet the aircraft landing requirements, such as Category I (CAT-I) Precision Approaches. However, the required accuracy can be achieved by augmenting the GPS. Among all these issues, the predominant factors that significantly influence the receiver position accuracy are selecting a user/receiver position estimation algorithm. In this article, a novel method is proposed based on correntropy and designated as Correntropy Kalman Filter (CKF) for precise GPS applications and GPS Aided Geosynchronous equatorial orbit Augmented Navigation (GAGAN) based aircraft landings over the low latitude Indian subcontinent. The real-world GPS data collected from a dual-frequency GPS receiver located in the southern region of the Indian subcontinent (IISc), Bangalore with Lat/Long: 13.021°N/ 77.5°E) is used for the performance evaluation of the proposed algorithm. Results prove that the proposed CKF algorithm exhibits significant improvement (up to 34%) in position estimation compared to the traditional Kalman Filter.

A Rapid Position Estimation Algorithm Inspired of Compound Eyes

2014 ◽  
Vol 43 (6) ◽  
pp. 612001
Author(s):  
邢强 XING Qiang ◽  
戴振东 DAI Zhendong ◽  
王浩 WANG Hao
Keyword(s):  
Estimation Algorithm ◽  
Position Estimation ◽  
Compound Eyes

scholarly journals Position Estimation of a PMSM in an Electric Propulsion Ship System Based on High-Frequency Injection

Electronics ◽  
2020 ◽  
Vol 9 (2) ◽  
pp. 276 ◽  
Author(s):  
Hongfen Bai
Keyword(s):  
Permanent Magnet ◽  
High Frequency ◽  
Electric Propulsion ◽  
Permanent Magnet Synchronous Motor ◽  
Estimation Algorithm ◽  
Synchronous Motor ◽  
Position Estimation ◽  
Second Order ◽  
Application Range ◽  
Rotor Position

To improve the operating performance of electric propulsion ships, the permanent magnet synchronous motor is commonly used as the propulsion motor. Additionally, position estimation without sensors can further improve the application range of the propulsion motor and the estimated results can represent the redundancy of measured values from mechanical sensors. In this paper, the high-frequency (HF) injection algorithm combined with the second-order generalized integrator (SOGI) is presented on the basis of analyzing the structure of the electric propulsion ship and the vector control of the motors. The position and rotor speed were estimated accurately by the approximate calculation of q-axis currents directly related to the rotor position. Moreover, the harmonics in the estimated position were effectively reduced by the introduction of the second-order generalized integrator. Then, the rotor position estimation algorithm was verified in MATLAB/Simulink by choosing different low speeds including speed reversal, increasing speed, and increasing load torque. Finally, the correctness of the proposed improved high-frequency injection algorithm based on the second-order generalized integrator was verified by the experimental propulsion permanent magnet synchronous motor (PMSM) system at low speed.

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