Xuebo Zhang

A Motion Planning-Based Adaptive Control Method for an Underactuated Crane System

This brief proposes a motion planning-based adaptive control strategy for an underactuated overhead crane system. To improve the transportation efficiency and enhance the safety of the crane system, the trolley is required to reach the desired position fast enough, while the swing of the payload needs to be within an acceptable domain. To achieve these objectives, a novel two-step design strategy consisting of a motion planning stage and an adaptive tracking control design stage, is proposed to control such an underactuated system as an overhead crane. Specifically, a novel desired trajectory, which satisfies physical constraints of an overhead crane, is proposed for the trolley by fusing theoretical analysis results with the conventional empirical trajectory planning methods. An adaptive control law is then constructed in the second step to make the trolley track the planned trajectory, where some online update mechanism is introduced to ensure that the controller works well with different working conditions. As shown by Lyapunov techniques, the proposed adaptive controller guarantees asymptotic tracking result even in the presence of uncertainties including system parameters and various disturbance. Some experiment results demonstrate that the proposed control method achieves superior performance for the underactuated cranes.

Adaptive Active Visual Servoing of Nonholonomic Mobile Robots

This paper presents a novel two-level scheme for adaptive active visual servoing of a mobile robot equipped with a pan camera. In the lower level, the pan platform carrying an onboard camera is controlled to keep the reference points lying around the center of the image plane. On the higher level, a switched controller is utilized to drive the mobile robot to reach the desired configuration through image feature feedback. The designed active visual servoing system presents such advantages as follows: 1) a satisfactory solution for the field-of-view problem; 2) global high servoing efficiency; and 3) free of any complex pose estimation algorithm usually required for visual servoing systems. The performance of the active visual servoing system is proven by rigorous mathematical analysis. Both simulation and experimental results are provided to validate the effectiveness of the proposed active visual servoing method.

Motion-Estimation-Based Visual Servoing of Nonholonomic Mobile Robots

A 2-1/2-D visual servoing strategy, which is based on a novel motion-estimation technique, is presented for the stabilization of a nonholonomic mobile robot (which is also called the “parking problem”). By taking into account the planar motion constraint of mobile robots, the proposed motion-estimation technique can be applied in both planar and nonplanar scenes. In addition, this approach requires no matrix estimation or decomposition, and it avoids ambiguity and degeneracy problems for the homography or fundamental matrix-based algorithms. Moreover, the field-of-view (FOV) constraint of the onboard camera is largely alleviated because the presented algorithm works well with few feature points. In order to incorporate the advantages of position-based visual servoing and image-based visual servoing, a composite error vector is defined that includes both image signals and the estimated rotational angle. Subsequently, a smooth time-varying feedback controller is adopted to cope with the nonholonomic constraints, which yields global exponential convergent rate for the closed-loop system. On the basis of the perturbed linear system theory, we show that practical exponential stability can be achieved, despite the lack of depth information, which is inherent for monocular camera systems. Both simulation and experiment results are collected to investigate the feasibility of the proposed approach.

Adaptive Tracking Control for an Overhead Crane System

Abstract This paper proposes an adaptive control method for an underactuated overhead crane system. To improve the transferring efficiency and enhance the security of the crane system, the trolley is required to reach the desired position as fast as possible, while the swing of payload needs to be within an acceptable domain. To achieve these objectives, a novel two-step design strategy consisting of a trajectory planning stage and an adaptive tracking control design stage, is proposed to attack such an underactuated system as overhead crane. In the first step this paper proposes a new S curve as the desired trajectory for trolley tracking, and in the second step, it constructs an adaptive control law to make the trolley track the planned trajectory. As shown by Lyapunov Techniques, the proposed adaptive controller guarantees an asymptotical tracking result even in the presence of uncertainties including system parameters and various disturbances. Simulation results demonstrate that the new S trajectory and the tracking controller achieves a superior performance for the underactuated cranes.

Visual servoing of nonholonomic mobile robots based on a new motion estimation technique

This paper presents a novel visual servoing strategy for a nonholonomic mobile robot, which is based on a new motion estimation technique. By taking into account the planar motion constraint of mobile robots, the proposed motion estimation technique does not require the estimation and decomposition of the homography or fundamental matrix, and it dose not cause any ambiguity problems. Moreover, the camera field-of-view (FOV) constraint and the partial occlusion problem are largely alleviated because the presented algorithm works well with few feature points. In order to incorporate the advantages of position-based visual servoing (PBVS) and image-based visual servoing (IBVS), a novel hybrid error vector is defined including both image signals and the estimated rotational angle. Furthermore, a smooth time-varying feedback controller is adopted to cope with the nonholonomic constraints, which yields global exponential stability for the closed-loop system despite the lack of depth information. Simulation results demonstrate the performance of the proposed approach.

Vision-Based Minimum-Time Planning of Mobile Robots with Kinematic and Visibility Constraints

Abstract This paper proposes a vision-based minimum-time trajectory planning method for mobile robots, which takes into account kinematic constraints for linear/angular velocities and accelerations, as well as the visibility constraint. Different from existing methods, by means of homography-based pose estimation, the vision-based trajectory planning is formulated as a constrained optimal control problem in the scaled Euclidean space, which is solved by using the Gauss Pseudospectral Method (GPM). Specifically, the homography matrix is estimated and then decomposed to obtain the relative rotation angle and the scaled translation between the current pose and the desired one, which are expressed in the scaled Euclidean space. Then, kinematic constraints are taken into account in this space, while the visibility constraint is formulated by mapping the Euclidean homography matrix to the image space. To our best of knowledge, it is the first reported approach to solve the vision-based minimum-time trajectory planning problem for wheeled mobile robots, which can help improve the working efficiency in realistic visual servoing systems. Extensive simulation and experimental results with comparison to other related methods are presented to demonstrate the effectiveness of the proposed approach.

An improved direct inverse modeling approach for high-speed feedforward tracking control of a piezoelectric tube actuator

To enhance the performance for high-speed tracking control of a piezoelectric tube actuator (PTA), an improved direct inverse rate-dependent PI model is obtained in this paper, and then adopted to design a practical feedforward controller achieving high-speed tracking control for a high-frequency trajectory with strong robustness. Specifically, based on the Prandtl-Ishlinskii (PI) model, an improved direct rate-dependent inverse model is set up for the PTA, with a polynomial function module introduced to eliminate the influence caused by the structure nonlinearity. Then, considering the features of the PTA structure, some preprocessing procedure is proposed to handle the collected experimental data, with the results utilized to identify all the unknown parameters over a wide bandwidth. Based on the obtained model, a practical feedforward controller, which presents the advantages of high-speed response, simple structure and convenient implementation, is then designed to enable the PTA to track high-frequency trajectories with satisfactory precision. Some experimental results are provided, which clearly demonstrate the high precision of the constructed/identified model, and the satisfactory performance of the proposed practical feedforward tracking control law.

Modeling and simulation for a 3D overhead crane

The dynamic model of a 3D overhead crane system is established by utilizing Lagrangepsilas equation. In the model, not only the motion of the trolley in horizontal plane, but also the variation of the rope length is considered, to provide a precise description for the dynamic performance of the system states. Furthermore, the main nonlinear disturbances existing in the environment, such as the dynamic and static mechanical frictions, air resistance and so on, are also included in the model. Based on the dynamic model, a simulation platform of a 3D overhead crane is constructed for further system analysis and controller design. Simulation results show the correctness of the dynamic model and the validity of the simulation platform.

A slope elimination method for AFM images based on the recurrent least square method

Atomic force microscopes (AFMs) are usually utilized for nano-scale imaging. Usually, the slide loading the samples and the stage of the AFM cannot be placed completely parallel with the motion plane of the piezoelectric actuator due to the manual operation and machining errors, which leads to the variation of imaging brightness (or height) along the slope and makes the relative topography unrealistic. Considering the fact that the introduced slopes are different for every imaging process, this paper proposes an effective and efficient real-time preprocessing approach for slope elimination, where the recurrent least square method is firstly utilized to estimate the slope, and the imaging method is then combined together to eliminate the slope and display the image in a real-time manner. Both simulation and experimental results demonstrate the superior performance of the proposed method.

An active visual servoing strategy for nonholonomic mobile robots

This paper presents a novel two-level scheme for active visual servoing of a mobile robot equipped with a pan camera. In the lower level, the pan platform carrying an on-board camera is controlled to keep the target points lying around the center of the image plane. On the higher level, a switched controller is utilized to drive the mobile robot to reach the desired configuration through image feature feedback. The designed active visual servo systems present such advantages as follows: i. a satisfactory solution for the field of view (FOV) problem; ii. global high servo efficiency; iii. free of any complex pose estimation algorithm usually required for visual servo systems. Simulation results are provided to validate the effectiveness of the proposed active visual servo method.