Robust visual tracking control system of a mobile robot based on a dual-Jacobian visual interaction model

Tsai, Chi-Yi; Song, Kai‐Tai; Dutoit, Xavier; Brussel, Hendrik Van; Nuttin, Marnix

doi:10.1016/j.robot.2009.01.001

Cited by 27 publications

(7 citation statements)

References 30 publications

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“…Klančar andŠkrjanc [44] proposed a model-predictive trajectory tracking control, where the linearized tracking error dynamics is used to predict the behavior of a WMR. Another solution of the trajectory tracking task was carried out by Tsai et al [45], where a robust visual tracking control to track a dynamic moving object was considered. Lee et al [46] carried out a sliding mode control by using an RFID sensor space to estimate the position of a WMR.…”

Section: Kinematic Modelmentioning

confidence: 99%

Tracking Control for Mobile Robots Considering the Dynamics of All Their Subsystems: Experimental Implementation

et al. 2017

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The trajectory tracking task in a wheeled mobile robot (WMR) is solved by proposing a three-level hierarchical controller that considers the mathematical model of the mechanical structure (differential drive WMR), actuators (DC motors), and power stage (DC/DC Buck power converters). The highest hierarchical level is a kinematic control for the mechanical structure; the medium level includes two controllers based on differential flatness for the actuators; and the lowest hierarchical level consists of two average controllers also based on differential flatness for the power stage. In order to experimentally validate the feasibility of the proposed control scheme, the hierarchical controller is implemented via a Σ-Δ-modulator in a differential drive WMR prototype that we have built. Such an implementation is achieved by using MATLAB-Simulink and the real-time interface ControlDesk together with a DS1104 board. The experimental results show the effectiveness and robustness of the proposed control scheme.

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Section: Kinematic Modelmentioning

confidence: 99%

Tracking Control for Mobile Robots Considering the Dynamics of All Their Subsystems: Experimental Implementation

et al. 2017

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“…Although robustness of servo controllers, like the two-stage controller proposed by Zhang et al (2017), can tolerate external disturbance to some extent, observer is an effective method to suppress external disturbance and image noise, thus improving performance of visual servoing systems. Tsai et al (2009) introduce a visual state estimator based on the self-tuning Kalman filter into the visual tracking system for the estimation of the system state and target motion in the image plane, by means of which a suitable observation covariance matrix is chosen automatically to reduce the influence of the environmental noise. Ma and Su (2015) apply the disturbance observer in the uncalibrated visual servoing approach to estimate and reject the model uncertainties, external disturbances and the noises.…”

Section: External Disturbance and Image Noisementioning

confidence: 99%

A survey on visual servoing for wheeled mobile robots

Wang

et al. 2021

Int J Intell Robot Appl

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Owing to advantages of large workspace and flexible movement, wheeled mobile robots are widely applied in industry. With vision module for environment perception, visual servoing of wheeled mobile robots has been one of the hottest research topics in robotic fields. Due to different demands for various applications and specific properties of the system, many challenges are faced for designing visual servoing control strategies. In this paper, development of visual servoing for mobile robots is elaborated in visual and control modules, respectively. The vision module along with various uncertainties are analyzed, which provides feedback signals for the servo controller, thus associating the image space with the motion space for further control. Moreover, motion controllers are devised under various constraints for different objectives, such as pose regulation and trajectory tracking. Research trends are discussed to show further focus of visual servoing of mobile robots.

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“…This paper focuses on the dynamic target tracking of the robot manipulator using visual servo method. The visual tracking control system for dynamic targets can be divided into visual state estimator and visual tracking controller in [12]. The visual state estimator can directly estimate the optimal system state and the object motion state in the image plane through the real-time observer.…”

Section: Introductionmentioning

confidence: 99%

Dynamic Visual Tracking for Robot Manipulator Using Adaptive Fading Kalman Filter

Zhang

Tang

et al. 2020

IEEE Access

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This paper focuses on the problem of visual tracking of a moving target with the temporary occlusion of image feature, a dynamic visual tracking control system for robot manipulator is developed by using adaptive fading Kalman filter (AFKF). The estimation of the residual covariance is used to compute the forgetting factor to automatically adjust the weight of the image observation data for improving the visual state estimation accuracy. When the target features are occluded, the prediction of missing observation sequence are generated by using the predicted compensation noise and preorder observation sequence to determine the forgetting factor for estimating the missing visual states. Then, a parameter adaptive law with projection error compensation is designed to realize the visual tracking with uncertain camera parameters. Finally, the trajectory tracking experiments based on a real robot platform is carried out to verify the performance of the proposed state estimator and tracking controller. The results show that the proposed method can accurately realize the visual tracking with the occluded trajectory and inaccurate camera parameters, which improves the flexibility of dynamic visual tracking of robot manipulator. INDEX TERMS Visual tracking, robot manipulation, Kalman filter, occlusion.

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Robust visual tracking control system of a mobile robot based on a dual-Jacobian visual interaction model

Cited by 27 publications

References 30 publications

Tracking Control for Mobile Robots Considering the Dynamics of All Their Subsystems: Experimental Implementation

Tracking Control for Mobile Robots Considering the Dynamics of All Their Subsystems: Experimental Implementation

A survey on visual servoing for wheeled mobile robots

Dynamic Visual Tracking for Robot Manipulator Using Adaptive Fading Kalman Filter

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