Nonlinear Attitude and Gyroscope's Bias Estimation for a Vtol Uav

Pflimlin, Jean Michel; Hamel, Tarek; Souères, Philippe; Metni, Najib

doi:10.3182/20050703-6-cz-1902.02008

Cited by 26 publications

(29 citation statements)

References 3 publications

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“…The first component is the direction towards the target and converges to a value close to 2. The second and third components should theoretically 4 See Pflimlin et al (2007) and Mahony et al (2005) for further information on the HoverEye attitude observation.…”

Section: Visual Servo Control For An Aerial Robot 321mentioning

confidence: 99%

Dynamic Image-Based Visual Servo Control For An Aerial Robot: Theory and Experiments

Mahony

Bras²,

Hamel

et al. 2008

UOPT

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This article considers the question of dynamic image-based visual servo control for a vertical take-off and landing unmanned aerial vehicle. The visual targets considered are colored blobs on a flat surface to which the normal direction is known. A fully nonlinear adaptive control design coupled with an asymptotic filter is provided that ensures the stability of the closed-loop system in a large domain. The image features used are a modified first order spherical moment for position regulation and optic flow for velocity damping.

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Section: Visual Servo Control For An Aerial Robot 321mentioning

confidence: 99%

Dynamic Image-Based Visual Servo Control For An Aerial Robot: Theory and Experiments

Mahony

Bras²,

Hamel

et al. 2008

UOPT

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“…Many low cost IMU are now internally compensated in temperature, and as a result, ω 0 oscillates slowly around a constant average value [9], reason why we consider it to be constant with the time. The term ω n is a Gaussian white noise.…”

Section: Fusion Of Sensors Estimationsmentioning

confidence: 99%

“…Even if the attitude estimation is a classical problem in mobile wheeled robotics [5], [6] and unmanned aerial vehicles (UAV) [7], [8], [9], several researchers have extended Open Solution for Humanoid Attitude Estimation P. Pierro, C. A. Monje, N. Mansard, P. Souères, C. Balaguer such techniques to legged locomotion [10], [11], [12], [13], [14].…”

Section: Introductionmentioning

confidence: 99%

Open Solution for Humanoid Attitude Estimation through Sensory Integration and Extended Kalman Filtering

et al. 2015

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In this paper an Extended Kalman Filter (EKF) is used in order to estimate the real state of a humanoid robot (HRP-2 robot in our case study) using the combination of the information coming from the encoders (kinematics) and from the Inertial Measurement Unit (IMU). The integration of the kinematic information into the Kalman filtering process allows a good estimation of the attitude and reduces the complexity of the problem to the use of simple kinematic transformations, even considering the existence of accelerations and mechanical flexibilities in the robot. The EKF estimator presented here is an open solution directly applicable to any humanoid robot, which is the main contribution of our approach. Experimental results are given showing the good performance of the method.Key words: Humanoid robot, Attitude estimation, Kalman filtering, Sensor integration, Kinematics simplicity Otvoreno rješenje za estimaciju položaja humanoidnog robota integracijom senzora i proširenim Kalmanovim filtrom. U ovomečlanku koristi se prošireni Kalmanov filtar (EKF) za estimaciju stanja humanoidnog robota (HRP-2 robot) kombiniranjem informacija iz enkodera (kinematika) i inercijalne mjerne jedinice (IMU). Integracijom kinematičkih informacija u proces Kalmanovog filtra ostvaruje se dobra estimacija položaja i smanjenje složenosti problema jednostavnim kinematičkim transformacijama,čak i u slučaju postojanja akceleracija te mehaničkih savijanja robota. EKF predstavljen u ovomečlanku otvoreno je rješenje primjenjivo na bilo kojem humanoidnom robotu, što je i glavni doprinos predloženog pristupa. Ekperimentalni rezultati pokazuju dobro ponašanje predložene metode.

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“…Kalman filters were also applied to the attitude estimation of accelerated rigid bodies in three dimensions from the fused measurements of gyroscopes and accelerometers [14]. In [15], a nonlinear observer for attitude estimation based on gyroscope measurements is described, but only kinematic relationships were considered in the model. A similar problem was solved in [16], where a nonlinear observer combined inertial and visual information.…”

Section: Previous Work In Verticality Estimationmentioning

confidence: 99%

On the benefits of head stabilization with a view to control balance and locomotion in humanoids

Farkhatdinov

Hayward

Berthoz

2011

2011 11th IEEE-RAS International Conference on Humanoid Robots

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Abstract-The estimation of the gravitational vertical is a fundamental problem faced by locomoting robots and animals alike. We describe a technique to address this problem that involves a damped inclinometer, an inertial measurement unit mounted on an actuated orienting platform, that is a robot head, so-to-speak. Simulations show that a nonlinear observer based on Newton's method to solve the full dynamics of the system given inertial sensor data gives accurate verticality estimates even in the presence of highly dynamic perturbations that include large fictitious force terms. Moreover, when the sensor platform is servoed to the estimate of the gravitational vertical to provide for horizontal stabilization, the accuracy of the estimate is improved by almost two orders of magnitude. Similar gains of performance are observed even in the presence of noise and parameter uncertainty.

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Nonlinear Attitude and Gyroscope's Bias Estimation for a Vtol Uav

Cited by 26 publications

References 3 publications

Dynamic Image-Based Visual Servo Control For An Aerial Robot: Theory and Experiments

Dynamic Image-Based Visual Servo Control For An Aerial Robot: Theory and Experiments

Open Solution for Humanoid Attitude Estimation through Sensory Integration and Extended Kalman Filtering

On the benefits of head stabilization with a view to control balance and locomotion in humanoids

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