Visual-inertial fusion for quadrotor Micro Air Vehicles with improved scale observability

Abeywardena, Dinuka; Wang, Zhan; Kodagoda, Sarath; Dissanayake, Gamini

doi:10.1109/icra.2013.6631015

Cited by 20 publications

(8 citation statements)

References 14 publications

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“…The accelerometer’s bias can be estimated online. In [25], the dynamic model was used to estimate the scale factor of monocular vision. In [26], a dynamic model/optical flow/inertial sensor fault-tolerant fusion method was proposed.…”

Section: Introductionmentioning

confidence: 99%

A Drag Model-LIDAR-IMU Fault-Tolerance Fusion Method for Quadrotors

Lyu

Wang

Lai

et al. 2019

Sensors

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In this paper, a drag model-aided fault-tolerant state estimation method is presented for quadrotors. Firstly, the drag model accuracy was improved by modeling an angular rate related item and an angular acceleration related item, which are related with flight maneuver. Then the drag model, light detection and ranging (LIDAR), and inertial measurement unit (IMU) were fused based on the Federal Kalman filter frame. In the filter, the LIDAR estimation fault was detected and isolated, and the disturbance to the drag model was estimated and compensated. Some experiments were carried out, showing that the velocity and position estimation were improved compared with the traditional LIDAR/IMU fusion scheme.

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Section: Introductionmentioning

confidence: 99%

A Drag Model-LIDAR-IMU Fault-Tolerance Fusion Method for Quadrotors

Lyu

Wang

Lai

et al. 2019

Sensors

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“… and Abeywardena et al. . However, the inherent drift of IMUs is prone to introducing estimation biases.…”

Section: Introductionmentioning

confidence: 99%

2D Relative Pose and Scale Estimation with Monocular Cameras and Ranging

2018

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Cooperative swarms of robots equipped with cameras are robust against failures and can explore Global Navigation Satellite System-denied environments efficiently. Applying Visual Simultaneous Localization and Mapping (VSLAM) techniques, vehicles can estimate their trajectories and simultaneously reconstruct the map of the environment using visual cues. Due to constraints on payload size, weight, and costs, many Visual Simultaneous Localization and Mapping applications must be based on a single camera. The associated monocular estimation of the trajectory and map is ambiguous by a scale factor. This work shows that by exploiting sparse range measurements between a pair of dynamic rovers in planar motion, the correct scale factors of both cameras and the relative position, as well as the relative attitude between the rovers, can be estimated. Neither images nor feature vectors are required to be transmitted over the communication channel for the proposed method, which is a significant advantage in practice.

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“…A number of approaches have been considered for resolving the global scale ambiguity. Most of them use IMUs, see for example Nützi et al [8] and Abeywardena et al [9]. However, the inherent drift of IMUs is prone to introducing estimation biases.…”

Section: Introductionmentioning

confidence: 99%

Scale and 2D Relative Pose Estimation of two Rovers using Monocular Cameras and Range Measurements

Zhu¹,

Giorgi²,

Günther³

2016

Proceedings of the 29th International Technical Meeting of the Satellite Division of the Institute of Navigation (ION GNSS+ 201

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is currently pursuing his Ph.D. at Technische Universität München as a full-time researcher at the Institute for Communications and Navigation. He received his B.Sc. in Automation Engineering from Tsinghua University, in Beijing, China in 2009, and his M.Sc. in Communications Engineering in 2011 from Technische Universität München, in Munich, Germany. His research interests include visual navigation, robotic swarm navigation, and multi-sensor fusion in autonomous vehicle navigation.

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Visual-inertial fusion for quadrotor Micro Air Vehicles with improved scale observability

Cited by 20 publications

References 14 publications

A Drag Model-LIDAR-IMU Fault-Tolerance Fusion Method for Quadrotors

A Drag Model-LIDAR-IMU Fault-Tolerance Fusion Method for Quadrotors

2D Relative Pose and Scale Estimation with Monocular Cameras and Ranging

Scale and 2D Relative Pose Estimation of two Rovers using Monocular Cameras and Range Measurements

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