Visual Servoing Of Mobile Robot Research Articles

Gaussian process-based cautious model predictive control for visual servoing of mobile robots

Gaussian process-based cautious model predictive control for visual servoing of mobile robots

Virtual-Goal-Guided RRT for Visual Servoing of Mobile Robots With FOV Constraint

In this article, a virtual-goal-guided rapidly exploring random tree (RRT)-based visual servoing approach is proposed for nonholonomic mobile robots to simultaneously satisfy the field-of-view (FOV) constraint and the velocity constraints during the motion toward the desired pose. The presented approach contains two parts: 1) trajectory planning in the scaled Euclidean space and 2) trajectory tracking control. For the trajectory planning part, a new virtual-goal-guided RRT algorithm is designed to guarantee the FOV constraint and the velocity constraints by iteratively exploring the scaled Euclidean space in the presence of unknown image depth. Specifically, a virtual goal directly behind the desired pose is set to guide the tree to extend laterally into the area wherein the robot is easier to satisfy the FOV constraint. In addition, the lateral extension of the tree also helps decrease the lateral error of the robot as much as possible. Following each successful extension toward the virtual goal node, a greedy extension from the newly explored node to the desired pose is attempted using a polar stabilization controller, so that the planned trajectory can accurately arrive at the desired pose. Each newly explored edge in the scaled space is projected into the image space to check for the FOV limit. For the visual tracking part, the final searched trajectory in the scaled space is first transformed into image feature trajectories, which are then tracked by an image-based visual tracking controller. Experiments validate the effectiveness of the proposed approach.

Wireless hybrid visual servoing of omnidirectional wheeled mobile robots

In this paper, we propose a new wireless hybrid control algorithm for visual servoing of mobile robots. In particular, the hybrid system is developed using the two autonomous control algorithms, i.e., position-based visual servoing (PBVS) and image-based visual servoing (IBVS). The PBVS algorithm is used for global routing, whereas the IBVS algorithm is used for the fine navigation. It helps in the specific steering towards the desired point for approaching the searched object. The proposed algorithm requires only the desired and actual poses of the mobile robot, and does not need any additional requirements such as the map of the environment or artificial landmarks. For the linearization of output signals, neural network extended Kalman filter is used. Several experimental as well as simulation results are presented in order to show the applicability of the proposed algorithm in the hybrid vision based control of mobile robots.

Visual servoing of mobile robots using non-central catadioptric cameras

This paper presents novel contributions on image-based control of a mobile robot using a general catadioptric camera model. A catadioptric camera is usually made up by a combination of a conventional camera and a curved mirror resulting in an omnidirectional sensor capable of providing 360° panoramic views of a scene. Modeling such cameras has been the subject of significant research interest in the computer vision community leading to a deeper understanding of the image properties and also to different models for different types of configurations. Visual servoing applications using catadioptric cameras have essentially been using central cameras and the corresponding unified projection model. So far only in a few cases more general models have been used. In this paper we address the problem of visual servoing using the so-called radial model. The radial model can be applied to many camera configurations and in particular to non-central catadioptric systems with mirrors that are symmetric around an axis coinciding with the optical axis. In this case, we show that the radial model can be used with a non-central catadioptric camera to allow effective image-based visual servoing (IBVS) of a mobile robot. Using this model, which is valid for a large set of catadioptric cameras (central or non-central), new visual features are proposed to control the degrees of freedom of a mobile robot moving on a plane. In addition to several simulation results, a set of experiments was carried out on Robot Operating System (ROS)-based platform which validates the applicability, effectiveness and robustness of the proposed method for image-based control of a non-holonomic robot.

Visual servoing of mobile robots for posture stabilization: from theory to experiments

SUMMARYOn the basis of the kinematic model of a unicycle mobile robot in polar coordinates, an adaptive visual servoing strategy is proposed to regulate the mobile robot to its desired pose. By regarding the unknown depth as model uncertainty, the system error vector can be chosen as measurable signals that are reconstructed by a motion estimation technique. Then, an adaptive controller is carefully designed along with a parameter updating mechanism to compensate for the unknown depth information online. On the basis of Lyapunov techniques and LaSalle's invariance principle, rigorous stability analysis is conducted. Because the control law is elegantly designed on the basis of the polar‐coordinate‐based representation of error dynamics, the consequent maneuver behavior is natural, and the resulting path is short. Experimental results are provided to verify the performance of the proposed approach. Copyright © 2013 John Wiley & Sons, Ltd.

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.

Passivity based visual servoing of mobile robots with dynamics compensation

This paper presents an image-based dynamic visual servoing to make a mobile robot able to track a moving object on the workspace by using a calibrated on board vision system. The stability of the proposed system is proved based on its passivity properties. A robustness analysis and an L2-gain performance analysis are also presented. Experimental results are shown to illustrate the system performance.