scholarly journals Complementary Filter Design Based Error Allocation for Attitude Estimation with Low-Cost Sensor

2018 ◽  
Author(s):  
Longhe Yang ◽  
Jianxin Ren ◽  
Kaiyue Song ◽  
Xiaofei Ma ◽  
Xinghui Yang
Keyword(s):  
Filter Design ◽  
Low Cost ◽  
Attitude Estimation ◽  
Complementary Filter

scholarly journals Nonlinear Complementary Filter for Attitude Estimation by Fusing Inertial Sensors and a Camera

Sensors ◽  
2020 ◽  
Vol 20 (23) ◽  
pp. 6752
Author(s):  
Lingxiao Zheng ◽  
Xingqun Zhan ◽  
Xin Zhang
Keyword(s):  
Inertial Sensors ◽  
Filter Design ◽  
Low Cost ◽  
Measurement Model ◽  
Attitude Estimation ◽  
System Stability ◽  
Feature Points ◽  
Complementary Filter ◽  
Geometry Measurement ◽  
Implicit Geometry

Using a standalone camera for pose estimation has been quite a standard task. However, the point correspondence-based algorithms require at least four feature points in the field of view. This paper considers the situation that there are only two feature points. Focusing on the attitude estimation, we propose to fuse a camera with low-cost inertial sensors based on a nonlinear complementary filter design. An implicit geometry measurement model is derived using two feature points in an image. This geometry measurement is fused with the angle rate measurement and vector measurement from inertial sensors using the proposed nonlinear complementary filter with only two parameters to be adjusted. The proposed nonlinear complementary filter is posed directly on the special orthogonal group SO(3). Based on the theory of nonlinear system stability analysis, the proposed filter ensures locally asymptotic stability. A quaternion-based discrete implementation of the filter is also given in this paper for computational efficiency. The proposed algorithm is validated using a smartphone with built-in inertial sensors and a rear camera. The experimental results indicate that the proposed algorithm outperforms all the compared counterparts in estimated accuracy and provides competitive computational complexity.

Fast Complementary Filter for Attitude Estimation Using Low-Cost MARG Sensors

2016 ◽  
Vol 16 (18) ◽  
pp. 6997-7007 ◽  
Author(s):  
Jin Wu ◽  
Zebo Zhou ◽  
Jingjun Chen ◽  
Hassen Fourati ◽  
Rui Li
Keyword(s):  
Low Cost ◽  
Attitude Estimation ◽  
Complementary Filter

Least square estimation-based adaptive complimentary filter for attitude estimation

2018 ◽  
Vol 41 (1) ◽  
pp. 235-245 ◽  
Author(s):  
Parag Narkhede ◽  
Alex Noel Joseph Raj ◽  
Vipan Kumar ◽  
Vinod Karar ◽  
Shashi Poddar
Keyword(s):  
Inertial Sensors ◽  
Low Cost ◽  
Attitude Estimation ◽  
Unmanned Vehicles ◽  
Least Square ◽  
Least Square Estimation ◽  
Micro Electro Mechanical Systems ◽  
Moving Vehicle ◽  
Complementary Filter ◽  
Filter Structure

Attitude estimation is one of the core fundamentals for navigation of unmanned vehicles and other robotic systems. With the advent of low cost and low accuracy micro-electro-mechanical systems (MEMS) based inertial sensors, these devices are used ubiquitously for all such commercial grade systems that need motion information. However, these sensors suffer from time-varying bias and noise parameters, which need to be compensated during system state estimation. Complementary filtering is one of such techniques that is used here for estimating attitude of a moving vehicle. However, the complementary filter structure is dependent on user fed gain parameters, KP and KI and needs a mechanism by which they can be obtained automatically. In this paper, an attempt has been made towards addressing this issue by applying least square estimation technique on the error obtained between estimated and measured attitude angles. The proposed algorithm simplifies the design of nonlinear complementary filter by computing the filter gains automatically. The experimental investigation has been carried out over several datasets, confirming the advantage of obtaining gain parameters automatically for the complementary filtering structure.

Complementary Filter Design with Three Frequency Bands: Robot Attitude Estimation

2015 ◽  
Author(s):  
Fernando Paulo Carreira ◽  
Joao Manuel Ferreira Calado ◽  
Carlos Batista Cardeira ◽  
Paulo Jorge Coelho Ramalho Oliveira
Keyword(s):  
Filter Design ◽  
Attitude Estimation ◽  
Frequency Bands ◽  
Complementary Filter

Attitude Estimation with Complementary Filter

2010 ◽  
Vol 44-47 ◽  
pp. 3781-3784
Author(s):  
Rui Hua Chang ◽  
Xiao Dong Mu ◽  
Xiao Wei Shen
Keyword(s):  
Solid State ◽  
Real Time ◽  
Inertial Sensors ◽  
Low Cost ◽  
Estimation Error ◽  
Estimation Method ◽  
Attitude Estimation ◽  
Complementary Filter

An attitude estimation method is presented for a robot using low-cost solid-state inertial sensors. The attitude estimates are obtained from a complementary filter by combining the measurements from the integration of a tri-axis gyro and an aiding system mechanized using a tri-axis accelerometer and a tri-axis magnetometer. The results show that the estimation error is less than 1 degree compare to the reference attitude. It is a simple, yet effective method for attitude estimation, suitable for real-time implementation on a robot.

Embedded Attitude Estimation System for Quad-Rotor UAVs

2013 ◽  
Vol 321-324 ◽  
pp. 528-531
Author(s):  
Jing Ran Wu ◽  
Zhen Guo Sun ◽  
Qi Dong Ma ◽  
Wen Zeng Zhang
Keyword(s):  
Real Time ◽  
Low Cost ◽  
Attitude Estimation ◽  
Mems Sensors ◽  
Autonomous Flight ◽  
The Real ◽  
Ground Testing ◽  
Complementary Filter ◽  
Estimation System

An embedded attitude estimation system is developed for the autonomous flight of Quad-Rotor UAVs. The system hardware is composed of a DSP processor and low-cost MEMS sensors including a 3-axis gyroscope and a 3-axis accelerometer. A Complementary Filter fused the advantages of the gyroscope and accelerometer is designed and embedded on the DSP processor to estimate the real-time attitude. Ground testing experiments show that the system could meet the accuracy and robustness requirements for the Quad-Rotor UAVs attitude estimation.

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