Visual servoing path-planning for approaching cylindrical objects

Eye-in-hand systems have received significant attention for the task of approaching an object identified by its reference image shown in advance. Image based visual servoing (VS) methods demonstrate robustness to image noises, but encounter difficulties especially when camera displacement is large. More challenges exist when the object is cylindrical with less texture. This paper proposes new feature set and pertinent trajectory planning scheme to achieve a convergent path with tolerable violation of camera field of view (FOV) limits, allowing transient loss of part of the observed object. Specifically, new features and interaction matrices are developed to achieve global convergence. Feature trajectories are then planned with tolerable FOV violation through a constrained nonlinear minimization path-planning technique. They are later tracked via an adapted IBVS controller in a switching manner. Simulation with two views of a real drinking vessel validates the proposed method and demonstrates its adaption to partial FOV violation.     

Robust adaptive visual tracking control for uncertain robotic systems with unknown dead-zone inputs

This paper is concerned with the image-based visual servoing (IBVS) control for uncalibrated camera-robot system with unknown dead-zone constraint, where the uncertain kinematics and dynamics are also considered. The control implementation is achieved by constructing a smooth inverse model for dead-zone-input to eliminate the nonlinear effect resulting from the actuator constraint. A novel adaptive algorithm, which does not require a priori knowledge of the parameter intervals of dead-zone model, is proposed to update the parameter values online, and the dead-zone slopes are not required the same. Furthermore, to accommodate the uncertainties of uncalibrated camera-robot system, adaptation laws are developed to estimate the uncertain parameters, simultaneously avoiding singularity of the image Jacobian matrix. With the full consideration of unknown dead-zone constraint and system uncertainties, an adaptive robust visual tracking control scheme together with dead-zone compensation is subsequently established such that the image tracking error converges to the origin. Based on a 3-DOF manipulator, simulations are conducted to verify the tracking performance of the proposed controller.     

New approach to visual servo control using terminal constraints

A large class of visual servo controllers relies on an a priori obtained reference image, captured at the desired position and orientation (i.e., pose) of a camera, to yield control signals to regulate the camera from its current pose to a desired pose. In many applications, accessibility and economics of the operation may prohibit acquisition of such a reference image. This paper introduces a new visual servo control paradigm that enables control of the camera in the absence of reference image using a set of terminal constraints. Specifically, the desired pose is encoded using the angle of obliquity of the optical axis with respect to the object plane and its direction of arrival at the plane. A constrained convex optimization problem is formulated over a conic section defined by the terminal constraints to yield an error system for the control problem. Subsequently, this work introduces continuous terminal sliding mode visual servo controllers to regulate the camera to the desired pose. Lyapunov-based stability analysis guarantees that the origin is a finite-time-stable equilibrium of the system. Numerical simulation results are provided to verify the performance of the proposed visual servo controller.     

Adaptive data-driven fault-tolerant control for nonlinear systems: Koopman-based virtual actuator approach

This paper proposes an adaptive data-driven fault-tolerant control scheme using the Koopman operator for unknown dynamics subjected to nonlinearities, time-varying loss of effectiveness, and additive actuator faults. The main objective of this method is to design a virtual actuator to hide actuator faults from the view of the system’s nominal controller without having any prior knowledge about the system’s underlying dynamics. The designed virtual actuator is placed between the faulty plant and the nominal controller of the system to keep the dynamical system’s performance consistent before and after the occurrence of actuator faults. Based on the Koopman operator theory, an equivalent Koopman predictor is first obtained using the process data only, without knowing the governing equations of the underlying dynamics. Koopman operator is an infinite-dimensional, linear operator which takes the nonlinear process data into an infinite-dimensional feature space where the dynamic data correlations have linear behavior. Next, based on the approximated system’s Koopman operator, a virtual actuator is designed and implemented without knowing the system’s nominal controller. Needless to use a separate fault detection, isolation, and identification module to perform fault-tolerant control, the current method leverages the adaptive framework to keep the system’s desired performance in facing time-varying additive and loss of effectiveness actuator faults. Finally, the approach’s efficacy is demonstrated using simulation on a two-link manipulator benchmark, and a comparison study is presented.     

Robust visual servoing control for quadrotors landing on a moving target

In this paper, a robust visual servoing control approach is proposed to address the landing problem for quadrotors on a moving platform. A vision system is implemented to estimate the position and velocity of the quadrotor. A robust cascade controller is proposed by following backstepping-like fundamentals and robust compensating theory. The effects of time-varying uncertainties, including parameter uncertainties and external disturbances, and time-varying delays resulted from image acquisition, image processing, and sensor measurement delays can be restrained. Experimental results using a quadrotor to land on a ground moving target illustrate the effectiveness of the proposed approach.     

Robust homography-based visual servo control for a quadrotor UAV tracking a moving target

In this study, a new robust homography-based visual tracking control approach for the quadrotor unmanned aerial vehicle (UAV) is developed. Specifically, employing the homography matrix as feedback, a hierarchical homography-based visual servoing (HBVS) scheme with a new command attitude extraction method to account for the underactuation of UAV is proposed. On this basis, a smooth hyperbolic tangent function is fulfilled as an augmented part of the backstepping control scheme, which guarantees the non-negative total thrust and avoid singularity. Additionally, a cascaded filter-based estimator and adaptive laws with integrable functions are embedded to counteract uncertainties including external perturbations, unknown acceleration of the moving target, and unknown image depth, and to facilitate the system’s asymptotic stability simultaneously. The theoretical analysis testifies that the whole close-loop system is asymptotically stable. Simulations further verify that the proposed HBVS controller can realize the visual tracking with a superior performance.     

Cooperative surrounding control with collision avoidance for networked Lagrangian systems

This paper investigates the cooperative surrounding control problem for networked multi-agent systems with nonlinear Lagrangian dynamics. With the consideration of the target with constant and time-varying velocity, two cooperative surrounding control algorithms with collision avoidance are proposed, in which possible collision among agents is prevented so as to achieve a more reliable and safer performance. For the case when the target has a constant velocity, a velocity observer is designed firstly for each agent. Secondly, to handle the nonlinear dynamics and avoid collisions, the neural networks and potential functions are used for the controller design. Then, the cooperative surrounding control algorithm is proposed such that all the agents surround the target with the desired relative positions. For the case when the target has a time-varying velocity, the velocity observer is designed under the assumption that the target’s partial acceleration is known for each agent. Then, the cooperative surrounding control algorithm is proposed such that the surrounding error between the target and each agent is bounded. The main difference between these two algorithms is that the former can ensure the collision avoidance among target and agents, while the latter can do so only among agents because the target’s velocity is time-varying. The Lyapunov theory is used to prove the stability of the cooperative surrounding control algorithms. The simulation illustrates the effectiveness of the theoretical results.     

Adaptive event-triggered control for uncalibrated visual servoing of robot manipulators

In the study, an adaptive event-triggered control strategy is proposed for image-based visual servoing of eye-to-hand robot manipulators, where the camera used does not need to be calibrated, and the dynamics behavior of manipulator is considered in design and analysis. To address the uncertainty in camera parameters and the nonlinearity in robot dynamics, and accommodate the errors between the real-time control signals and the piecewise-constant event-triggered control signals, a new and novel robust adaptive estimation approach is developed, and well fused with visual feedback control design so that the boundedness of all closed-loop signals, and the asymptotic convergence of image error towards zero are established simultaneously. Besides rigorous proof in theory, the obtained results are also confirmed by comparative simulation tests.     

Finite-time sliding mode attitude control for rigid spacecraft without angular velocity measurement

The continuous finite-time nonsingular terminal sliding mode (NTSM) attitude tracking control for rigid spacecraft is investigated. Firstly, a finite-time attitude controller combined with a new adaptive update law is designed. Different from existing controllers, the proposed controller is inherently continuous and the chattering is effectively reduced. Then, an adaptive model-free finite-time state observer (AMFFTSO) and an angular velocity calculation algorithm (AVCA) are developed to estimate the unknown angular velocity. The unique feature of the proposed method is that the finite-time estimation of angular velocity is achieved and no prior knowledge of quaternion derivative upper bound is needed. Next, based on the estimated angular velocity, a finite-time attitude controller with only attitude measurement is developed. Finally, some simulations are presented and the effectiveness of the proposed control scheme is illustrated.     

Novel neuromuscular controller application method to improve the balance recovery ability of lower limb exoskeletons

In recent years, several biological frameworks have been proposed to imitate human motion and control lower limb exoskeletons. Compared with position or impedance tracking of defined joint trajectories, this kind of strategy can reproduce human walking dynamics, and tolerate external disturbance. The output of this kind of strategy is anticipatory feedforward torque, which means that the controller needs to have sufficient prior knowledge on neurology. Moreover, lower limb exoskeletons are fundamentally different from humans, which weakens the ability of the controller to resist external internal interference. Thus, pure feedforward control hardly achieves a flexible movement like that of a human. In this study, we propose a feedback control framework based on repetitive learning control (RLC) to enhance the anti-interference capability of a neuromuscular controller. The controller consists of two parts: (1) A data-driven morphed nonlinear phase oscillator is used as a state observer to learn the changing law of an exoskeleton’s posture and center of mass and to construct a stable limit cycle in the state space. (2) A posture and centroid tracker based on RLC is utilized to track the output of oscillators and achieve a natural balance recovery process. Simulation and experimental results show that the integrated control system has a better control effect than the simple biological control method.     

L’ Hopital’S rule-Based adaptive dynamic surface control for a class of strict-Feedback systems with unknown parameters

In this paper, a L’ Hopital’s rule-based adaptive dynamic surface control (L-ADSC) scheme is developed for a class of strict-feedback systems with unknown parameters using backstepping technique. The L-ADSC-derived backstepping technique is deployed to remove differentiation of complex virtual controller, thereby efficiently avoiding ”exlosion of complexity”. The L’ Hopital’s Rule is resorted to tackle singularity problem within controller synthesis. As a consequence, the proposed L-ADSC scheme guarantees that all signals of the closed-loop control system are semi-globally uniformly ultimately bounded. Simulation results show remarkable effectiveness.     

匀速运动模糊图像恢复的离散化模型研究

图像恢复是图像处理领域的热点问题之一。利用导致图像退化的先验知识,沿着图像退化逆过程进行恢复。根据运动模糊图像的成像原理,建立了运动模糊图像的退化模型,结合图像复原的基本数学模型,运用积分变换以及微分数值化方法,建立了匀速运动模糊图像恢复的离散化过程,最后推导给出了匀速运动模糊图像恢复的离散化数学模型。该模型只利用了产生模糊的相关参数以及能够获取的退化图像信息,结果简单直接,对于后续相关算法设计提供了理论上的支撑。     

Finite-time target localization and multicircular circumnavigation with bearing-only measurements

This paper studies the finite-time localization and multicircular circumnavigation problem of an unknown stationary target via a networked multi-agent system using bearing-only measurements. To enhance the convergence rate of estimation, a novel estimator is developed to enable the agent to localize the target in finite time. At the same time, with the estimated target position, a distributed controller is designed such that the agents circumnavigate the target along different orbits with any prescribed angular spacing in finite time. In terms of Lyapunov theory and cascade control strategy, finite-time stability of the overall system including the estimator and controller are analyzed rigorously. Besides, the proposed algorithms guarantee that the agents can keep a safe distance from the target in the whole movement process, and high angular velocity can be avoided even if the circumnavigation radius becomes small. Finally, to corroborate the theoretical results, two simulation examples are given.     

Driver and automation cooperation approach for share steering control system

The interferences and drivers' maloperations are important factors affecting vehicle driving safety. This paper investigates the problem of authority allocation to weaken the impact of interferences and drivers’ maloperations on the shared steering control system. Based on the parallel framework of the shared steering control system, an extended framework including the upper level and the lower lever is proposed. The lower lever is used to realize the shared steering control, which includes the driver model, trajectory tracking controller and vehicle model. To improve the robustness of the system, the uncertainty of vehicle dynamics parameters is considered in the trajectory tracking controller, including tire cornering stiffness and longitudinal velocity. The upper level is used to calculate the authority level of the driver and controller required by the lower lever, which consists of an authority dynamic allocation model and an authority allocation decision strategy. The role of the authority dynamic allocation model is to calculate the reference allocation level of the driver and controller dynamically. When the driver's operation and vehicle working states are trustworthy, the reference allocation levels of the driver and controller will be followed. Conversely, a decision result will be gained by the authority allocation decision strategy to replace the reference allocation levels, and the sum of the authority levels of the driver and the automation will not be fixed as 1. The simulation results show that the proposed approach can effectively improve vehicle driving safety, anti-interference and reliability, and can effectively reduce the impact of crosswind and driver's maloperation on vehicle safety, and alleviate the driver's operation load.     

The cognitive selection framework for knowledge acquisition strategies in virtual communities

As a significant source of knowledge, virtual communities have stimulated interest in knowledge management research. Nonetheless, very few studies to date have examined the demand-side knowledge perspective such as knowledge acquisition in virtual communities. In order to explore the knowledge acquisition process within virtual communities, this study proposes the cognitive selection framework of knowledge acquisition strategy in virtual communities. The proposed framework takes a cognitive perspective, to identify how knowledge recipients select their strategy for acquiring specialized knowledge, emphasizing their cognitive goals (e.g., cognitive replication and innovation) and cognitive motivators (e.g., virtual community self-efficacy, heightened enjoyment, and time resources). Our results suggest that knowledge recipients’ cognitive motivators differentially influence their cognitive goals (cognitive replication and innovation), which, in turn, are related to their selection of knowledge acquisition strategy (static and dynamic acquisition strategy), respectively.     

社会资本和个人动机对虚拟社区知识共享影响的研究

从虚拟社区知识共享行为的动因出发,来探索虚拟社区社会资本和个人动机的影响,构建虚拟社区社会资本和个人动机对知识共享影响的理论模型,提出相关假设。对虚拟社区成员进行问卷调查,对得到的293份有效问卷的样本数据,运用LISREL 8.8和SPSS 17.0进行验证性分析,检验了研究假设。实证研究表明,社会资本和个人动机对虚拟社区成员的知识共享行为有显著的正向影响。研究结果对了解虚拟社区知识共享行为,实现基于网络平台的个性化知识管理与服务策略有重要参考意义。     

基于不变矩的海面红外目标识别

针对焦平面红外探测器对海面目标进行探测所得到的红外图像，提出一种基于不变矩的海面红外目标识别的方法。该方法采用空间域处理和基于灰度相似性的区域分割来提取目标区域，计算其七不变矩值，利用目标区域的面积大小、矩阵组数值等作为先验知识，对识别目标进行识别。此方法经过了实测图像的检验，正确识别率为94.53%。     

三维影像靶射击系统设计

传统的射击训练由于受经费、场地、安全等因素影响,很难在群众中普及.本文结合大屏幕投影、人机交互等虚拟现实技术,设计了一个虚拟影像靶射击训练系统.在一个大屏幕投影系统中,射击者手持模拟枪械对虚拟的三维影像靶射击,系统利用红外摄像头对射击位置进行实时检测,判断是否击中目标.在射击过程中,场景与射击者是相对变化的,增强了射击...     

Circular formation control for cooperative target tracking with limited information

This paper addresses the problem of encircling and tracking a moving target with a fleet of unicycle-like vehicles. A new control law is developed to steer the vehicles to an evenly spaced formation along a circumference, the center of which tracks the motion of the target. The strategy proposed relies only on the relative positions of the agents with respect to the target, expressed in the local frame of each vehicle. The absolute position, velocity and acceleration of the target are unknown. Additionally, the robustness of the proposed control law in the presence of external disturbances is analyzed. Communication among agents is used to maintain the vehicles equally spaced in the circular formation. Simulation results illustrate the effectiveness of the proposed strategies.     

Formation control for a string of interconnected second-order systems via target feedback

This paper investigates the formation control of interconnected second-order systems. Each agent is assumed to be capable of measuring its own absolute velocity and the relative positions with respect to its neighboring agents, whereas the target formation is described by absolute positions of all agents in a global coordinate. For such formation control problems, no distributed control policy was reported in existing literature. This paper focuses on the string connection structure of the agents and proposes a distributed control policy that takes the form of purely state feedback without incorporating any feed-forward component. The closed-loop system equation is characterized by an oscillation matrix whose entries are the feedback controller gains. Formation control is accomplished by formulating the agents’ target positions as feedback controller gains. Moreover, it is shown that for agent models described by double integrators, each of the agents located at the two endpoints of the string structure should know its own absolute position. For a class of agent models where each agent’s acceleration depends on its own position, the control laws do not need to use the absolute position. For both system models, the target formations that are asymptotically reachable by the proposed control laws are specified explicitly. Numerical simulations have been conducted to illustrate the effectiveness of the theoretical results.