Bio: Jin Wang is an academic researcher from Chongqing University of Posts and Telecommunications. The author has contributed to research in topics: Adaptive control & Visual servoing. The author has an hindex of 1, co-authored 1 publications receiving 69 citations.
TL;DR: A novel two-stage controller is proposed by using adaptive control and backstepping methods that works well even with both unknown extrinsic camera-to-robot parameters and unknown depth.
Abstract: In this paper, a monocular visual servoing strategy is presented for nonholonomic mobile robots. Different from existing methods, the proposed approach works well even with both unknown extrinsic camera-to-robot parameters and unknown depth. Considering these unknown parameters, the mathematical model of an eye-in-hand mobile robot becomes an uncertain nonholonomic system which violates the conventional triangularity condition, as a result, the stabilization problem is very challenging and still unsolved. Therefore, a novel two-stage controller is proposed by using adaptive control and backstepping methods. In the first stage, adaptive velocity controllers are carefully designed to drive the angular error and the lateral error to an arbitrarily small neighborhood of zero, and asymptotic convergence is proven using Lyapunov-based techniques. Afterwards, a proportional controller is applied to regulate the longitudinal error in the second stage. Experimental results are provided to verify the effectiveness of the proposed approach.
TL;DR: Under the proposed algorithm, not only can the consensus of CVs be guaranteed but also the behavior of vehicles is consistent with traffic flow theory.
Abstract: This paper proposes a distributed nonlinear consensus delay-dependent control algorithm for a connected vehicle (CV) platoon. In particular, considering that the behavior of the following vehicle is associated with the longitudinal inter-vehicle gap with respect to the preceding vehicle, a nonlinear function is designed to characterize the car-following interactions between CVs. Then, a nonlinear consensus algorithm is proposed by incorporating the car-following interactions and heterogeneous time delays. The delay-dependent convergence condition of the proposed control algorithm is analyzed using the Lyapunov–Krasovskii method, and an estimate of the delay bound is provided. Under the proposed algorithm, not only can the consensus of CVs be guaranteed but also the behavior of vehicles is consistent with traffic flow theory. Finally, an example using a 10-vehicle platoon is provided under three scenarios: no time delays, heterogeneous time delays, and homogeneous time delays. Results from extensive simulations verify the effectiveness of the proposed control algorithm in terms of the position, velocity, and acceleration/deceleration profiles.
TL;DR: A new solution for the control problem related to trajectory tracking in a differential drive wheeled mobile robot (DDWMR) is presented and the performance achieved is better than, or at least similar to, performance achieved with the average controller reported in literature.
Abstract: By using the hierarchical controller approach, a new solution for the control problem related to trajectory tracking in a differential drive wheeled mobile robot (DDWMR) is presented in this paper. For this aim, the dynamics of the three subsystems composing a DDWMR, i.e., the mechanical structure (differential drive type), the actuators (DC motors), and the power stage (DC/DC Buck power converters), are taken into account. The proposed hierarchical switched controller has three levels: the high level corresponds to a kinematic control for the mechanical structure; the medium level includes two controls based on differential flatness for the actuators; and the low level is linked to two cascade switched controls based on sliding modes and PI control for the power stage. The hierarchical switched controller was experimentally implemented on a DDWMR prototype via MATLAB-Simulink along with a DS1104 board. With the intention of assessing the performance of the switched controller, experimental results associated with a hierarchical average controller recently reported in literature are also presented here. The experimental results show the robustness of both controllers when parametric uncertainties are applied. However, the performance achieved with the switched controller introduced in the present paper is better than, or at least similar to, performance achieved with the average controller reported in literature.
TL;DR: In this article, a dynamics-level finite-time fuzzy monocular visual servo (DFFMVS) scheme is created for regulating an unmanned surface vehicle (USV) to the desired pose.
Abstract: In this article, in the presence of completely unknown dynamics and unmeasurable velocities, a dynamics-level finite-time fuzzy monocular visual servo (DFFMVS) scheme is created for regulating an unmanned surface vehicle (USV) to the desired pose. Main contributions are as follows: first, with the aid of homography decomposition, a novel homography-based visual servo structure for a USV with both kinematics and dynamics is first established such that complex unknowns including unmeasurable poses and velocities, image depth, system dynamics, and time-varying inertia are sufficiently encapsulated; second, using finite-time observer technique, finite-time velocity observer (FVO) based visual-servo error dynamics are elaboratively formulated, and thereby facilitating backstepping synthesis; third, by virtue of the FVO, the adaptive fuzzy dynamics approximator together with adaptive residual feedback is deployed to compensate complex unknowns, and thereby contributing to accurate regulation of pose errors; and fourth, a completely model-free monocular visual servo approach only using a camera is eventually invented. Simulation studies on a benchmark prototype USV demonstrate that the proposed DFFMVS scheme has remarkable performance with significant superiority in both visual servo and unknowns observation.
TL;DR: An acceleration-level pseudo-dynamic visual servoing structure for the nonholonomic mobile robots is proposed, based on which two different adaptive controllers are designed—backstepping and dynamic surface control (DSC) in the presence of unknown depth information.
Abstract: In this paper, we propose an acceleration-level pseudo-dynamic visual servoing structure for the nonholonomic mobile robots, based on which we design two different adaptive controllers—backstepping and dynamic surface control (DSC) in the presence of unknown depth information. Different from existing kinematic controllers, which directly regard linear and angular velocities as control inputs, this paper designs acceleration control that is integrated to easily obtain smooth velocity signals to be accurately executed by the robot. Two controllers are designed and analyzed with Lyapunov techniques: 1) a backstepping controller yielding asymptotical stability and 2) a dynamic surface controller ensuring system errors to be ultimately uniformly bounded. The unknown depth is handled by designing an adaptive parameter estimation law in both methods. Finally, a comparison between backstepping and DSC is given based on the experimental results and the design procedures.
TL;DR: An adaptive visual servoing scheme is developed to drive a wheeled mobile robot to the desired pose, wherein the unknown depth information is identified simultaneously and the pose regulation errors and the depth identification error can converge to zero simultaneously.
Abstract: In this paper, an adaptive visual servoing scheme is developed to drive a wheeled mobile robot to the desired pose, wherein the unknown depth information is identified simultaneously. Specifically, system errors are selected by measurable signals at first, then the kinematics model is obtained in polar coordinates containing the unknown feature depth. On the basis of the concurrent learning strategy, an augmented adaptive updating law is constructed for the unknown feature depth using both recorded and current data. Then, the regulation controller is designed with polar-coordinate representation to drive the mobile robot to the desired pose under the nonholonomic motion constraint. Subsequently, rigorous stability analysis is conducted by utilizing Lyapunov techniques and LaSalle's invariance principle, demonstrating that the pose regulation errors and the depth identification error can converge to zero simultaneously. The performance of the proposed visual servoing method is further validated by both simulation and experimental results.