Vision-Based Tracking Control of Quadrotor With Backstepping Sliding Mode Control

Zhao, Zhiqiang; Tang, Yang; Wu, Chunping; Du, Wei

doi:10.1109/access.2018.2882241

Cited by 20 publications

(11 citation statements)

References 33 publications

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“…The main challenge is propagating errors from motion compensation to tracking which produces further detection errors and is, eventually, computationally expensive. Interest in studying motion capture with moving cameras has increased with the development of cameras mounted on unmanned aerial vehicles (UAVs) [29], [30]. Although, because of their ever-changing FOVs, using moving cameras for motion capture is a very challenging problem, when both the object and cameras are moving almost parallel to each other, this problem is alleviated to some extent.…”

Section: Related Workmentioning

confidence: 99%

Stereo Vision-Based 3D Positioning and Tracking

et al. 2020

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The evolution of technologies for the capture of human movement has been motivated by a number of potential applications across a wide variety of fields. However, capturing human motion in 3D is difficult in an outdoor environment when it is performed without controlled surroundings. In this paper, a stereo camera rig with an ultra-wide baseline distance and conventional cameras with fish-eye lenses is proposed. Its cameras provide a wide field of view (FOV) which increases the coverage area and also enables the baseline distance to be increased to cover the common area required for both cameras' views to perform as a stereo camera. We propose a passive marker-based approach to track the motion of the object. In this method, an adaptive thresholding method is applied to extract each small pink polyester marker from the video frames. As the cameras have fish-eye lenses, it is difficult to estimate the depth information using a pinhole camera model. We use a unique method to restore the 3D positions by developing a relationship between the pixel dimensions and distances in an image and real world coordinates. In this paper, occlusion detection is considered because, in the marker-based capturing of articulated human kinematics, the occlusion of a marker is one of the major challenges. The detection algorithm differentiates among types of occlusions and predicts any missing marker position where necessary. As this design is intended to be mounted on a moving carrier, such as a drone or car, a method for compensating the camera's ego-motion is proposed. The proposed 3D positioning and tracking system is tested in different situations to validate its applicability as a stereo camera rig as well as its performance for motion capture. The performance of the proposed system is compared with that of a standard motion capture system called Vicon and is shown to have the same order of accuracy while incurring less cost. INDEX TERMS Motion capture, 3D positioning, stereo vision, motion tracking, high precision.

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Section: Related Workmentioning

confidence: 99%

Stereo Vision-Based 3D Positioning and Tracking

et al. 2020

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“…Theorem 3: Distributed consensus control for system (23) can be decomposed into the form of formation control and the weighted sum form of all adjacent formation distance controllers, as given in (33), which can achieve the finite-time first-order consensus shown in (15) and (16).…”

Section: Distributed Consensus Control Algorithm For Multiple Quadmentioning

confidence: 99%

“…With the advantages of strong robustness, low chattering and quick response, SMC has attracted a large number of researchers for improvement, so as to achieve better convergence, higher response speed and lower chattering. An adaptive SMC is designed in [15] based on the back-stepping technique with the advantages of simplicity in design and ease of application. An adaptive super-twisting sliding model algorithm (STA) is provided in [16] to reduce the control effort as well as the chattering effect.…”

Section: Introductionmentioning

confidence: 99%

An Adaptive Distributed Consensus Control Algorithm Based on Continuous Terminal Sliding Model for Multiple Quad Rotors’ Formation Tracking

Jiu

Sun

et al. 2019

IEEE Access

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Distributed consensus formation tracking problem of slow convergence and low accuracy for multiple quad rotors are solved in this paper. Continuous nonsingular terminal sliding model algorithm (CNTSMA) under Inner-Outer loop control structure is considered to deal with the control problem of nonlinear, strong coupling and underactuated characteristic of a quad rotor. For better convergence and higher tracking accuracy, an adaptive algorithm (denoted by ACNTSMA) further focused on coupling of x and y directions, with sliding model observer (SMO) to compensate system disturbances and uncertainties is proposed. Furthermore, to solve the consensus formation tracking problem, a consensus control protocol under a full-connected topology based on ACNTSMA is proposed, including formation pattern consensus controller and formation distance consensus controller. Stability theory and simulation results prove the proposed control algorithm is able to accurately achieve the first-order (position and velocity) consensus for multiple quad rotors' formation tracking. Besides, stability analysis of the proposed consensus control protocol illustrates that all sliding modes with finite-time stability applicable to second-order integral models are supposed to be established. And the proposed controller also has better convergence and faster response speed with no chattering for trajectory tracking. INDEX TERMS Distributed formation tracking, consensus, continuous terminal sliding model algorithm, adaptive algorithm, multiple quad rotors, convergence.

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“…PBVS methods rely on relative pose estimation techniques, including the PnP algorithm, epipolar geometry, ICP algorithm, or the fusion of vision and other sensors. In [13], a monocular semi-direct visual odometry algorithm was applied to obtain position information and an adaptive sliding mode controller based on the backstepping technique was presented for quadrotor tracking control. In [14], visual feedback was exploited to estimate the position and attitude of a UAV based on the triangulation method, and a classical PID control was designed for indoor UAV flight.…”

Section: Introductionmentioning

confidence: 99%

Robust Vision-Based Control of a Rotorcraft UAV for Uncooperative Target Tracking

Zhang

Zhao

Zhou

2020

Sensors

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This paper investigates the problem of using an unmanned aerial vehicle (UAV) to track and hover above an uncooperative target, such as an unvisited area or an object that is newly discovered. A vision-based strategy integrating the metrology and the control is employed to achieve target tracking and hovering observation. First, by introducing a virtual camera frame, the reprojected image features can change independently of the rotational motion of the vehicle. The image centroid and an optimal observation area on the virtual image plane are exploited to regulate the relative horizontal and vertical distance. Then, the optic flow and gyro measurements are utilized to estimate the relative UAV-to-target velocity. Further, a gain-switching proportional-derivative (PD) control scheme is proposed to compensate for the external interference and model uncertainties. The closed-loop system is proven to be exponentially stable, based on the Lyapunov method. Finally, simulation results are presented to demonstrate the effectiveness of the proposed vision-based strategy in both hovering and tracking scenarios.

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Vision-Based Tracking Control of Quadrotor With Backstepping Sliding Mode Control

Cited by 20 publications

References 33 publications

Stereo Vision-Based 3D Positioning and Tracking

Stereo Vision-Based 3D Positioning and Tracking

An Adaptive Distributed Consensus Control Algorithm Based on Continuous Terminal Sliding Model for Multiple Quad Rotors’ Formation Tracking

Robust Vision-Based Control of a Rotorcraft UAV for Uncooperative Target Tracking

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