Supervisory Control of Multirotor Vehicles in Challenging Conditions Using Inertial Measurements

Bangura, Moses; Hou, Xiaolei; Allibert, Guillaume; Mahony, Robert; Michael, Nathan

doi:10.1109/tro.2018.2864788

Cited by 11 publications

(3 citation statements)

References 48 publications

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“…Using this drag model, wind gust are estimated using EKF with barometer [16] and with GPS [17]. Bangura et al in [18] proposed a simple but state-of-the-art control and state estimation of attitude, inertial and body-fixed frame linear velocities that only requires IMU and barometer sensor systems. Additionally, when inertial measurements are available using GPS or vision system, it can estimate wind velocity as the offset between inertial and body-fixed frame linear velocities transformed into the same frame reference.…”

Section: A Review Of Related Workmentioning

confidence: 99%

Frequency-Based Wind Gust Estimation for Quadrotors Using a Nonlinear Disturbance Observer

Asignacion

Suzuki

Noda

et al. 2022

IEEE Robot. Autom. Lett.

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In city-wide weather prediction, wind gust information can be obtained using unmanned aerial vehicles (UAVs). Although wind sensors are available, an algorithm-based active estimation can be helpful not only as a weightless substitute but also as feedback for robust control. This paper aims to estimate the wind gusts affecting the quadrotors (a type of UAV) as the input disturbances by using a frequency-based nonlinear disturbance observer (NDOB). To obtain highly accurate estimations, frequency is considered as the main design parameter, thereby focusing the estimation on the frequency range of the wind gusts. The NDOB is developed using the Takagi-Sugeno (T-S) fuzzy framework. In this approach, the twelfth-order nonlinear model is approximated into a sixth-order T-S fuzzy model to reduce computational cost. A two-step verification method is presented, which includes MATLAB/Simulink simulations and the experiments performed using a 2.5 kg quadrotor.

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Section: A Review Of Related Workmentioning

confidence: 99%

Frequency-Based Wind Gust Estimation for Quadrotors Using a Nonlinear Disturbance Observer

Asignacion

Suzuki

Noda

et al. 2022

IEEE Robot. Autom. Lett.

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“…In the literature on drone navigation, there are numerous successful solutions based on the fusion of inertial sensors with exteroceptive sensors based on the visible or infrared spectra such as monocular cameras [9], [10], stereo cameras [11], [12], or lidars [13]. This comes however with some disadvantages, such as the computational cost for extracting features with cameras requiring the images to be processed off-board on a computer station or on-board using a dedicated integrated circuit [9], [14], and the obstruction of the sensors in case of difficult environmental conditions (dust, fog, varying ambient light). These solutions are thus not adapted to our use-case of the pipings mapping with a microdrone, which requires a low computational cost in order to maximize battery life and the ability to work in a potentially visually-obstructed environment.…”

Section: Introductionmentioning

confidence: 99%

Micro-Drone Ego-Velocity and Height Estimation in GPS-Denied Environments Using an FMCW MIMO Radar

Barra¹,

Creuzet²,

Lesecq³

et al. 2023

IEEE Sensors J.

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In the context of autonomous navigation, the vehicle trajectory estimation and the detection of surrounding obstacles are two critical functionalities that must be robust to difficult environmental conditions (e.g. fog, dust, snow) and the unavailability of infrastructure signals (e.g. GPS). With the advantage of remaining operable in low-visibility conditions, radar sensors are good candidates to detect obstacles in an autonomous navigation context. In this paper, we show that radars can also be successfully used for real-time trajectory estimation. We address the case of an autonomous micro-drone intended for the exploration of piping networks and embedding a Frequency Modulated Continuous Waves (FMCW) MIMO radar. We show that using a beamforming technique to virtually steer the radar field-of-view, we can simultaneously estimate the horizontal and vertical velocity of the drone as well as its height. These results are first validated through simulations based on experimental drone flight data and a radar simulator. Then, using an Infineon 77GHz FMCW radar, we show through real-world experiments the high performance attainable with our solution.

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“…Multi-sensor approaches can be considered the main research direction for navigation and positioning [1]. Hybrid positioning techniques often involve Inertial Measurement Units (IMUs) [2], [3], and visual sensors [4]- [6]. For what concerns fault management methods, several works focus on integrity monitoring [1], [7], [8].…”

Section: Introductionmentioning

confidence: 99%

GNSS-Imaging Data Fusion for Integrity Enhancement in Autonomous Vehicles

Baldoni

Battisti

Brizzi

et al. 2022

IEEE Trans. Aerosp. Electron. Syst.

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The transport sector is experiencing a fast and revolutionary development, moving towards the deployment of autonomous vehicles. Thus, the accuracy of the position information and the integrity of the navigation system have become key factors. In this paper, we address the problem of the enhancement of the integrity of the position provided by a Global Navigation Satellite System receiver by exploiting sensor fusion. To this aim, we estimate the lateral offset and heading of the vehicle with respect to a georeferenced roadway centerline from the images supplied by an on-board camera. Moreover, we perform integrity monitoring based on the implementation of the Solution Separation in the parity space. The numerical results indicate that the use of sensor fusion and digital map allows to attain a longitudinal Protection Level reduction with respect to the case in which sensor fusion is not exploited. More specifically, a decrease of about 70% is achieved when a single constellation is used, while reduction is less relevant, about 15%, when two constellations are employed.

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Supervisory Control of Multirotor Vehicles in Challenging Conditions Using Inertial Measurements

Cited by 11 publications

References 48 publications

Frequency-Based Wind Gust Estimation for Quadrotors Using a Nonlinear Disturbance Observer

Frequency-Based Wind Gust Estimation for Quadrotors Using a Nonlinear Disturbance Observer

Micro-Drone Ego-Velocity and Height Estimation in GPS-Denied Environments Using an FMCW MIMO Radar

GNSS-Imaging Data Fusion for Integrity Enhancement in Autonomous Vehicles

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