Xinwu Liang

Adaptive Image-Based Trajectory Tracking Control of Wheeled Mobile Robots With an Uncalibrated Fixed Camera

In this paper, the uncalibrated image-based trajectory tracking control problem of wheeled mobile robots will be studied. The motion of the wheeled mobile robot can be observed using an uncalibrated fixed camera on the ceiling. Different from traditional vision-based control strategies of wheeled mobile robots in the fixed camera configuration, the camera image plane is not required to be parallel to the motion plane of the wheeled mobile robots and the camera can be placed at a general position. To guarantee that the wheeled mobile robot can efficiently track its desired trajectory, which is specified by the desired image trajectory of a feature point at the forward axis of the wheeled mobile robot, we will propose a new adaptive image-based trajectory tracking control approach without the exact knowledge of the camera intrinsic and extrinsic parameters and the position parameter of the feature point. To eliminate the nonlinear dependence on the unknown parameters from the closed-loop system, a depth-independent image Jacobian matrix framework for the wheeled mobile robots will be developed such that unknown parameters in the closed-loop system can be linearly parameterized. In this way, adaptive laws can be designed to estimate the unknown parameters online, and the depth information of the feature point can be allowed to be time varying in this case. The Lyapunov stability analysis will also be performed to show asymptotical convergence of image position and velocity tracking errors of the wheeled mobile robot. The simulation results based on a two-wheeled mobile robot will be given in this paper to illustrate the performance of the proposed approach as well. The experimental results based on a real wheeled mobile robot will also be provided to validate the proposed approach.

Visual Servoing of Soft Robot Manipulator in Constrained Environments With an Adaptive Controller

It is unavoidable for a soft manipulator to interact with environments during some tasks. These interactions may affect the soft manipulator and make the kinematic model different from the one in free space, e.g., the soft manipulators effective length and the target positions might change. In order to apply the soft manipulator to constrained environments, an adaptive visual servo controller based on piecewise-constant curvature kinematic, without knowing the true values of the manipulators length and the target positions, is proposed in this paper. Experimental results in the free space, constrained environment, and the gravity-influenced environment, demonstrate the convergence of the image errors under the proposed controller.

Adaptive Task-Space Cooperative Tracking Control of Networked Robotic Manipulators Without Task-Space Velocity Measurements

In this paper, the task-space cooperative tracking control problem of networked robotic manipulators without task-space velocity measurements is addressed. To overcome the problem without task-space velocity measurements, a novel task-space position observer is designed to update the estimated task-space position and to simultaneously provide the estimated task-space velocity, based on which an adaptive cooperative tracking controller without task-space velocity measurements is presented by introducing new estimated task-space reference velocity and acceleration. Furthermore, adaptive laws are provided to cope with uncertain kinematics and dynamics and rigorous stability analysis is given to show asymptotical convergence of the task-space tracking and synchronization errors in the presence of communication delays under strongly connected directed graphs. Simulation results are given to demonstrate the performance of the proposed approach.

Adaptive Vision-Based Leader–Follower Formation Control of Mobile Robots

This paper focuses on the problem of vision-based leader–follower formation control of mobile robots. The proposed adaptive controller only requires the image information from an uncalibrated perspective camera mounted at any position and orientation (attitude) on the follower robot. Furthermore, the approach does not depend on the relative position measurement and communication between the leader and follower. First, a new real-time observer is developed to estimate the unknown intrinsic and extrinsic camera parameters as well as the unknown coefficients of the plane where the feature point moves relative to the camera frame. Second, the Lyapunov method is employed to prove the stability of the closed-loop system, where it is shown that convergence of the image error is guaranteed. Finally, the performance of the approach is demonstrated through physical experiments and experimental results.

Shape Detection Algorithm for Soft Manipulator Based on Fiber Bragg Gratings

The shape of soft a manipulator cannot be sensed by the operator directly, when applied to rescue of mine disaster, science exploration, or minimally invasive surgery due to the narrow and closed environment. Shape information is sometimes important for the soft manipulator to be controlled. In order to deal with the problem of shape sensing, a shape sensing algorithm and sensor network based on Fiber Bragg Gratings (FBGs) are introduced in this paper. The shape sensing algorithm is based on piecewise constant curvature and torsion assumption, and can translate the curvature and torsion measured by sensor network into global positions and orientations of nodes. Three-dimensional experiments show that the algorithm introduced in this paper can achieve high accuracy for 3-D shapes.

Three-Dimensional Dynamics for Cable-Driven Soft Manipulator

A soft manipulator usually has infinite joints. The infinite DOFs of a soft manipulator make it impossible to build the mechanical model like traditional rigid manipulator. The dynamic model based on circular arcs assumption, proposed by previous literature, does not take torsion into consideration. The introduction of torsion to piecewise constant curvature assumption could improve accuracy for 3-D motion, but it still cannot deal with problems with normal strain and viscidity of soft material, especially when the Youngs Modulus is small. In this paper, by combining the geometrically exact Cosserat rod theory and Kelvin model, a new mechanical model for a silicone rubber soft manipulator is proposed. Two vectors, curvature vector and strain vector, are used to depict the bending and torsion effect, and normal strain. Both 2-D and 3-D experiments are performed to verify the mechanical model.

Leader-Following Formation Tracking Control of Mobile Robots Without Direct Position Measurements

Most existing formation control approaches assume that accurate global or local position measurements of the robots are directly available, without giving details about how to obtain these measurements, or only providing Kalman filter-type estimators to get them without considering effects of the estimation on the closed-loop system stability. Hence, developing formation controllers with position estimators that can guarantee overall closed-loop system stability becomes highly desirable. This technical note presents a new formation tracking controller for the nonholonomic mobile robots without using direct position measurements. To deal with the absence of accurate position measurements, feedback information from a perspective camera, the odometry and Attitude and Heading Reference System (AHRS) sensors is used to design an observer to provide online estimates of the relative position of the follower with respect to the leader. Using Lyapunov stability analysis, we show that the combined observer-controller closed-loop system is stable, and both the formation tracking errors and the relative position estimation errors asymptotically converge to zero. The performance of the proposed scheme is illustrated through experimental results.

A unified design method for adaptive visual tracking control of robots with eye-in-hand/fixed camera configuration

A unified design method is proposed in this paper to handle adaptive visual tracking control problem of robots. In the proposed scheme, the robot dynamic parameters, camera intrinsic and extrinsic parameters and position parameters of feature points are assumed to be uncertain. A unified kinematics model is presented to simultaneously cope with kinematics modeling problem of robots with the eye-in-hand or fixed camera configuration. Based on the unified kinematics, a unified design method is proposed to solve the visual tracking control problem of robots with the eye-in-hand or fixed camera configuration. By using the depth-independent interaction matrix framework, adaptive laws are derived to handle the unknown parameters. Lyapunov stability analysis is provided to show asymptotical convergence of image position and velocity tracking errors. To show the effectiveness of the proposed unified design method, experimental results for both camera configurations are also given.

Adaptive image-based visual servoing of wheeled mobile robots with fixed camera configuration

In this paper, we will study the uncalibrated vision-based positioning problem of wheeled mobile robots by using a ceiling-mounted camera. A new image-based visual servoing scheme will be proposed, which can cope with the unknown intrinsic and extrinsic parameters of the camera and the uncertain distance parameter of the feature point from geometric center of the mobile robot. The presented approach is developed via extending the depth-independent interaction matrix framework for robot manipulators to mobile robots such that the nonlinear dependence on unknown parameters can be removed from the image-Jacobian matrix and then, we can linearly parameterize uncertain parameters in the closed-loop system. In this way, an estimation scheme for the online updating of uncertain parameters can be developed very efficiently. To show that image errors can be guaranteed to be asymptotically convergent, stability analysis will be carried out by using Lyapunov theory. To validate the performance of the presented approach, simulation and experimental results will also be provided.

Image-Based Visual Servoing of a Quadrotor Using Virtual Camera Approach

In this paper, an image-based visual servoing control law is proposed for a quadrotor unmanned aerial vehicle using an on-board monocular camera and an inertial measurement unit sensor. Based on the perspective projection model, suitable image features are defined on a rotated image plane called virtual image plane, thus a decoupled image feature dynamics is achieved. Then, a translational velocity observer is presented using these image features. The image feature dynamics and quadrotor dynamics are combined to derive a nonlinear controller. The controller is based on backstepping technique to account for the underactuation of the quadrotor. The image-based visual servoing controller only needs three point features, which make it useable in general environment. The closed-loop system is proved globally asymptotic stable by means of Lyapunov analysis. Computer simulations that regulate a quadrotor to a desired position with respect to (w.r.t.) four points lying on a horizontal plane and three points lying on a full rotated slope are conducted separately. Smooth and efficient trajectories are obtained both in virtual image plane and Cartesian space. Finally, experimental tests including pushing and pulling the visual target are conducted to verify the validity and robustness of the proposed controller. The proposed control law regulates the quadrotor to a desired position, defined by desired image, from an unknown initial position, which can be used in monitoring, landing, and other applications.