{'fraction_non_alphanumeric': 0.024808033077377438, 'fraction_numerical': 0.01004134672179563, 'mean_word_length': 5.033254156769596, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 1, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Special Issue on “Vision‐Based Control Systems”

Vision-based control systems can be defined as systems that employ visual information for decision and control. With the advances in computing and computer vision technologies, vision feedback has been used in many modern control systems to improve robustness to modelling uncertainty and to provide useful information for autonomous task execution in an unstructured or unknown environment. The use of vision feedback in the control loop presents new challenges for the design and analysis of the control system. Beyond expertise in a specific discipline, vision-based control approach also requires multidisciplinary expertise to integrate a vision system with the controller for various tasks. Many visual servoing methods have been proposed in the literature of robotics (e.g., [1–7]). Several papers that provide excellent tutorials and survey in visual servoing of robots can be found in [3,5,6]. Most visual servoing methods are designed at the kinematic level where the control commands are robot velocities and the effects of the nonlinear dynamics are neglected. Though much progress had been obtained in dynamic control of robots [8,9] in 1980s, the uncertainty of the Jacobian matrix due to camera calibration errors and kinematic uncertainty posed a challenging dynamic control problem which was only formally solved in the late 1990s [10]. Since then, many vision based controllers or sensory feedback controllers with uncertain Jacobian matrix, which take the robot dynamics into consideration in the design and analysis of the closed-loop control systems, have been proposed (e.g. [11–16]). A summary of the works on dynamic vision based control of robot can be found in [17]. Although there have been many contributions to the research and development of vision based control systems, many emerging research areas and applications remain to be explored. This special issue brings together 14 papers to highlight some of the recent developments in vision based control systems. In the first paper, Yang and Liu propose a robust vision based tracking algorithm for estimation of beating heart motion in presence of disturbances such as visual occlusion. The proposed algorithm allows 3D coordinates of a point of interest of heart motion to be extracted for motion compensation and control in robotic heart surgery. The second paper by Mebarki and Lippiello deals with an aerial manipulation problem. An image-based servo control scheme is presented for simultaneous control of both the unmanned aerial vehicle and the onboard manipulator. Gu et. al. consider cooperative vision based tracking problem of 3D moving targets by using two mobile agents. An optimal condition is derived for the cooperative observation problem. The next three papers in this special issue deal with the vision based control problems of wheeled mobile robots. MacKunis et al. develop a control method to achieve unified tracking and regulation visual servo control for a wheeled mobile robot. Ou et al. investigate the finite-time control problem of nonholonomic mobile robots in presence of parametric uncertainty associated with the camera system. Chen et al. address the visual servo control problem of wheeled mobile robot with consideration of saturated inputs. The effects of dynamics in vision based control systems are considered in the next two papers. Dirksz et al. utilize the port-Hamiltonian approach to formulate an image-based visual servo controller for dynamic systems. Liang et. al. present an image-based adaptive controller for electrically driven robot, with consideration of both robot and actuator dynamics. Jurado et al. investigate vision-based 3D trajectory tracking control problem using a RGB-D camera and applied the method to an emulated quadrotor unmanned aerial vehicle. Li et al. employed feedback linearization, linear quadratic regulation, and nonlinear optimization techniques to develop a tracking control method for a 3-DOF helicopter by utilizing only an onboard monocular camera. Oliveira et. al. present a visual servoing scheme for robot manipulator with uncalibrated camera, based on sliding mode control and switching monitoring scheme. The last three papers in this special issue deal with some interesting vision based control applications. Zhu et. al. develop a vison based reagent dosage control system for a copper flotation plant. Su et. al. develop vision based navigation problem of mobile agent based on computational intelligence techniques. Chang et al. design a hybrid force and vision-based controller for a six-DOF robotic manipulator to achieve target localization in conformal radiotherapy. We are grateful to all authors and reviewers for their contributions and help to this special issue. Last but not least, we thank the Editor-in-Chief, Li-Chen Fu, for his support for this special issue. Guest Editors Chien Chern Cheah Asian Journal of Control, Vol. 16, No. 3, pp. 629–631, May 2014 Published online in Wiley Online Library (wileyonlinelibrary.com) DOI: 10.1002/asjc.908