scholarly journals Single axis FOG aided attitude estimation algorithm for mobile robots

Mechatronics ◽  
2015 ◽  
Vol 30 ◽  
pp. 158-173 ◽  
Author(s):  
B. Allotta ◽  
R. Costanzi ◽  
F. Fanelli ◽  
N. Monni ◽  
A. Ridolfi
Keyword(s):  
Mobile Robots ◽  
Estimation Algorithm ◽  
Attitude Estimation

scholarly journals An Attitude Estimation Algorithm for Mobile Robots Under Unknown Magnetic Disturbances

2016 ◽  
Vol 21 (4) ◽  
pp. 1900-1911 ◽  
Author(s):  
Riccardo Costanzi ◽  
Francesco Fanelli ◽  
Niccolo Monni ◽  
Alessandro Ridolfi ◽  
Benedetto Allotta
Keyword(s):  
Mobile Robots ◽  
Estimation Algorithm ◽  
Attitude Estimation ◽  
Magnetic Disturbances

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.

Reliable attitude estimation algorithm considering atypical observation

2021 ◽  
Vol 65 (10) ◽  
Author(s):  
Xiao-Ting Guo ◽  
Chong Shen ◽  
Jun Tang ◽  
Jie Li ◽  
Jun Liu
Keyword(s):  
Estimation Algorithm ◽  
Attitude Estimation

High-precision roll attitude estimation of decoupled canards relative to the projectile body using bipolar hall-effect sensors

2021 ◽  
pp. 1-9
Author(s):  
Tingting Yin ◽  
Zhong Yang ◽  
Youlong Wu ◽  
Fangxiu Jia
Keyword(s):  
Hall Effect ◽  
Real Time ◽  
High Precision ◽  
Solution Method ◽  
Estimation Method ◽  
Estimation Algorithm ◽  
Attitude Estimation ◽  
Fuzzy Algorithms ◽  
Positioning Method ◽  
Hall Effect Sensors

The high-precision roll attitude estimation of the decoupled canards relative to the projectile body based on the bipolar hall-effect sensors is proposed. Firstly, the basis engineering positioning method based on the edge detection is introduced. Secondly, the simplified dynamic relative roll model is established where the feature parameters are identified by fuzzy algorithms, while the high-precision real-time relative roll attitude estimation algorithm is proposed. Finally, the trajectory simulations and grounded experiments have been conducted to evaluate the advantages of the proposed method. The positioning error is compared with the engineering solution method, and it is proved that the proposed estimation method has the advantages of the high accuracy and good real-time performance.

scholarly journals A DCM Based Attitude Estimation Algorithm for Low-Cost MEMS IMUs

2015 ◽  
Vol 2015 ◽  
pp. 1-18 ◽  
Author(s):  
Heikki Hyyti ◽  
Arto Visala
Keyword(s):  
Kalman Filter ◽  
Extended Kalman Filter ◽  
Low Cost ◽  
Direction Cosine ◽  
Estimation Algorithm ◽  
Calibration Method ◽  
Attitude Estimation ◽  
Mems Sensors ◽  
Acceleration Sensors ◽  
Adaptive Extended Kalman Filter

An attitude estimation algorithm is developed using an adaptive extended Kalman filter for low-cost microelectromechanical-system (MEMS) triaxial accelerometers and gyroscopes, that is, inertial measurement units (IMUs). Although these MEMS sensors are relatively cheap, they give more inaccurate measurements than conventional high-quality gyroscopes and accelerometers. To be able to use these low-cost MEMS sensors with precision in all situations, a novel attitude estimation algorithm is proposed for fusing triaxial gyroscope and accelerometer measurements. An extended Kalman filter is implemented to estimate attitude in direction cosine matrix (DCM) formation and to calibrate gyroscope biases online. We use a variable measurement covariance for acceleration measurements to ensure robustness against temporary nongravitational accelerations, which usually induce errors when estimating attitude with ordinary algorithms. The proposed algorithm enables accurate gyroscope online calibration by using only a triaxial gyroscope and accelerometer. It outperforms comparable state-of-the-art algorithms in those cases when there are either biases in the gyroscope measurements or large temporary nongravitational accelerations present. A low-cost, temperature-based calibration method is also discussed for initially calibrating gyroscope and acceleration sensors. An open source implementation of the algorithm is also available.

Highly Efficient Attitude-Estimation Algorithm for Star Trackers Using Optimal Image Matching

2013 ◽  
Vol 36 (6) ◽  
pp. 1672-1680 ◽  
Author(s):  
Tjorven Delabie ◽  
Joris De Schutter ◽  
Bart Vandenbussche
Keyword(s):  
Image Matching ◽  
Estimation Algorithm ◽  
Attitude Estimation ◽  
Highly Efficient

scholarly journals Evaluation of Murrell’s EKF-Based Attitude Estimation Algorithm for Exploiting Multiple Attitude Sensor Configurations

Sensors ◽  
2021 ◽  
Vol 21 (19) ◽  
pp. 6450
Author(s):  
Sharanabasaweshwara Asundi ◽  
Norman Fitz-Coy ◽  
Haniph Latchman
Keyword(s):  
Magnetic Field ◽  
Time Derivative ◽  
Estimation Algorithm ◽  
Field Vector ◽  
Attitude Estimation ◽  
Magnetic Field Vector ◽  
Sun Sensor ◽  
Satellite Attitude ◽  
Multiple Sensor ◽  
Sensor Suite

Pico- and nano-satellites, due to their form factor and size, are limited in accommodating multiple or redundant attitude sensors. For such satellites, Murrell’s implementation of the extended Kalman filter (EKF) can be exploited to accommodate multiple sensor configurations from a set of non redundant attitude sensors. The paper describes such an implementation involving a sun sensor suite and a magnetometer as attitude sensors. The implementation exploits Murrell’s EKF to enable three sensor configurations, which can be operationally commanded, for satellite attitude estimation. Among the three attitude estimation schemes, (i) sun sensor suite and magnetometer, (ii) magnetic field vector and its time derivative and (iii) magnetic field vector, it is shown that the third configuration is better suited for attitude estimation in terms of precision and accuracy, but can consume more time to converge than the other two.

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