Design and implementation of a low-cost observer-based attitude and heading reference system

Martin, Philippe; Salaün, Erwan

doi:10.1016/j.conengprac.2010.01.012

Cited by 150 publications

(108 citation statements)

References 14 publications

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“…This would make it possible to avoid our proposed method to tune the measurement covariance of accelerometers and to improve the accuracy of the proposed filter, as it would no longer be vulnerable to nontemporary or constant accelerations. Many velocity aided attitude estimation methods are dependent on measurement of linear velocity in addition to gyro and accelerometer measurements in order to reliably compensate for nongravitational accelerations [31][32][33][34]. Instead of using velocity measurements, we use only a low-cost triaxial set of an accelerometer and a gyroscope.…”

Section: Related Workmentioning

confidence: 99%

“…Most of these consist of various Kalman filter solutions [2,3,5,12,13,16,25], usually extended Kalman filters (EKF) [7,9,10,15,17,18,20,26], and some unscented Kalman filters (UKF) [14,19,27], though some non-Kalman filter solutions also exist [1,4,11,21,[28][29][30] as well as some geometric methods [31][32][33][34]. In addition, Chao et al [35] have carried out a comparative study of low-cost IMU filters.…”

Section: Related Workmentioning

confidence: 99%

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

Hyyti

Visala

2015

International Journal of Navigation and Observation

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An attitude estimation algorithm is developed using an adaptive extended Kalman filter for low-cost microelectromechanicalsystem (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.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

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

Hyyti

Visala

2015

International Journal of Navigation and Observation

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“…Measurements from accelerometers, gyroscopes and magnetometers mounted onboard the multirotor helicopter are recorded at a rate of 200 Hz. The algorithm proposed in [23] is utilised to combine these sensor measurements to produce attitude estimates. The desired rotor angular velocities and rotor tilt angle are also updated a rate of 200 Hz.…”

Section: Experimental Analysismentioning

confidence: 99%

Modelling and Daisy Chaining Control Allocation of a Multirotor Helicopter with a Single Tilting Rotor

2016

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This paper presents the development and implementation of a single tilting rotor multirotor helicopter. A single tilting rotor multirotor helicopter is proposed that allows for decoupled lateral acceleration and attitude states. A dynamics model of the proposed multirotor helicopter is established to enable control system development. A control system architecture and daisy chaining-based control allocation scheme is developed and implemented. The control architecture facilitates the control of decoupled lateral accelerations and attitudes. Further, a computational and experimental analysis is undertaken and offers evidence that the proposed multirotor helicopter and control system architecture enables the multirotor helicopter to achieve lateral accelerations without requiring attitude actuation.

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“…A relevant approach that is closely related to invariant observer is the complementary filter [33], which is designed directly on the matrix representation of the special orthogonal group SO (3). The invariant observer method is applied to the design of low-cost AHRS in [34][35][36], and is further used in the GPS-aided inertial navigation system for outdoor MAV applications in [37][38][39]. In addition, examples of complementary filter-based visual/inertial state estimation of a helicopter MAV can be found in [40].…”

Section: Related Workmentioning

confidence: 99%

Invariant Observer-Based State Estimation for Micro-Aerial Vehicles in GPS-Denied Indoor Environments Using an RGB-D Camera and MEMS Inertial Sensors

Tang³

et al. 2015

Micromachines

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This paper presents a non-linear state observer-based integrated navigation scheme for estimating the attitude, position and velocity of micro aerial vehicles (MAV) operating in GPS-denied indoor environments, using the measurements from low-cost MEMS (micro electro-mechanical systems) inertial sensors and an RGB-D camera. A robust RGB-D visual odometry (VO) approach was developed to estimate the MAV's relative motion by extracting and matching features captured by the RGB-D camera from the environment. The state observer of the RGB-D visual-aided inertial navigation was then designed based on the invariant observer theory for systems possessing symmetries. The motion estimates from the RGB-D VO were fused with inertial and magnetic measurements from the onboard MEMS sensors via the state observer, providing the MAV with accurate estimates of its full six degree-of-freedom states. Implementations on a quadrotor MAV and indoor flight test results demonstrate that the resulting state observer is effective in estimating the MAV's states without relying on external navigation aids such as GPS. The properties of computational efficiency and simplicity in gain tuning make the proposed invariant observer-based navigation scheme appealing for actual MAV applications in indoor environments. OPEN ACCESSMicromachines 2015, 6 488

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Design and implementation of a low-cost observer-based attitude and heading reference system

Cited by 150 publications

References 14 publications

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

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

Modelling and Daisy Chaining Control Allocation of a Multirotor Helicopter with a Single Tilting Rotor

Invariant Observer-Based State Estimation for Micro-Aerial Vehicles in GPS-Denied Indoor Environments Using an RGB-D Camera and MEMS Inertial Sensors

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