Stereo Tracking and Servoing for Space Applications

This paper proposes a real-time, robust and efficient three-dimensional (3-D) model-based tracking algorithm for visual servoing. A virtual visual servoing approach is used for 3-D tracking. This method is similar to more classical nonlinear pose computation techniques. Robustness is obtained by integrating an M-estimator into the virtual visual control law via an iteratively reweighted least-squares implementation. The presented approach is also extended to the use of multiple cameras. Results show the method to be robust to occlusion, changes in illumination and mistracking.     

Wrist Camera-Based Vibration Suppression Control for a Flexible Manipulator

This paper addresses a vision-based method for estimating vibration excited in the tip of a flexible-link manipulator. In this method, estimation of vibration is achieved by observing the variation of image features projected on a wrist camera. It mimics the situation of utilizing a wrist camera in tip vibration control of a space manipulator. In space, a vision sensor can be expected to be a feasible means for measuring the elastic vibration of the space manipulators, since they are more reliable compared with sensors like strain gauges. The method proposed in this paper takes advantage of the frequential characteristics of visual information that are reflected as a blurred background scene. With the high-frequency component of the projected image features, a Kalman filter-based observer is implemented as the estimator for the vibration. This implementation is characterized by the considerations of incorporating the slow sensor of the camera in the fast servo loop and compensation of the time delay due to image processing. With the vibration estimator, vibration suppression control relying solely on a wrist camera becomes possible. This scheme is successfully verified by experiments.     

Efficient model-based tracking for robot vision

This paper proposes a real-time, robust and efficient three-dimensional (3D) model-based tracking algorithm. A virtual visual servoing approach is used for monocular 3D tracking. This method is similar to more classical non-linear pose computation techniques. A concise method for derivation of efficient distance-to-contour interaction matrices is described. An oriented edge detector is used in order to provide real-time tracking of points normal to the object contours. Robustness is obtained by integrating a M-estimator into the virtual visual control law via an iteratively re-weighted least-squares implementation. The method presented in this paper has been validated on several visual servoing experiments considering various objects. Results show the method to be robust to occlusion, changes in illumination and mis-tracking.     

Optimal Camera Trajectory under Visibility Constraint in Visual Servoing: A Variational Approach

The principal deficiency of an image-based servo is that the induced three-dimensional (3-D) trajectories are not optimal and sometimes, especially when the displacements to realize are large, these trajectories are not physically valid, leading to the failure of the servoing process. In this paper, we adress the problem of generating trajectories of some image features that correspond to optimal 3-D trajectories in order to control efficiently a robotic system using an image-based control strategy. First, a collineation path between given the start and end points is obtained, and then the trajectories of the image features are derived. Path planning is formulated as a variational problem that allows us to consider simultaneously optimality and inequality constraints (visibility). A numerical method is employed for solving the path planning problem in the variational form.     

Motion Planning Strategy for Finding an Object with a Mobile Manipulator in Three-Dimensional Environments

In this paper, we investigate the problem of minimizing the average time required to find an object in a known three-dimensional environment. We consider a 7-d.o.f. mobile manipulator with an 'eye-in-hand' sensor. In particular, we address the problem of searching for an object whose unknown location is characterized by a known probability density function. We present a discrete formulation, in which we use a visibility-based decomposition of the environment. We introduce a sample-based convex cover to estimate the size and shape of visibility regions in three dimensions. The resulting convex regions are exploited to generate trajectories that make a compromise between moving the manipulator base and moving the robotic arm. We also propose a practical method to approximate the visibility region in three dimensions of a sensor limited in both range and field of view. The quality and success of the generated paths depend significantly on the sensing robot capabilities. In this paper, we generate searching plans for a mobile manipulator equipped with a sensor limited in both field of view and range. We have implemented the algorithm and present simulation results.     

Augmented Nonlinear PD Controller for a Redundantly Actuated Parallel Manipulator

In order to improve trajectory tracking accuracy for a redundantly actuated parallel manipulator, a so-called augmented nonlinear PD (ANPD) controller based on the conventional dynamic controller is proposed in this paper. The ANPD controller is designed by replacing the linear PD in the augmented PD controller with a nonlinear PD algorithm. The stability of the parallel manipulator system with the proposed ANPD controller is proven using the Lyapunov stability theorem, and the ANPD controller is further proven to guarantee asymptotic convergence to zero of both the tracking error and error rate. The superiority of the ANPD controller is verified through trajectory tracking experiments of an actual 2-d.o.f. redundantly actuated parallel manipulator.     

Visual Odometry for a Hopping Rover on an Asteroid Surface using Multiple Monocular Cameras

Visual odometry refers to the use of images to estimate the motion of a mobile robot. Real-time systems have already been demonstrated for terrestrial robotic vehicles, while a near real-time system has been successfully used on the Mars Exploration Rovers for planetary exploration. In this paper, we adapt this method to estimate the motion of a hopping rover on an asteroid surface. Due to the limited stereo depth resolution and the continuous rotational motion on a hopping rover, we propose to use a system of multiple monocular cameras. We describe how the scale of the scene observed by different cameras without overlapping views can be transferred between the cameras, allowing us to reconstruct a single continuous trajectory from multiple image sequences. We describe the implementation of our algorithm and its performance under simulation using rendered images.     

空间机械臂在轨维修的视觉伺服操控策略

首先分析了空间机械臂/机械手系统在轨旋拧螺钉任务的尺寸链误差．为修正微重力环境和机械臂、模拟维修单机在轨安装导致的位姿偏差,特别是消除机械手抓取电动工具导致的随机误差影响,提出了航天员在轨标定电动工具位姿/全局相机测量电动工具位姿并引入机械臂进行视觉伺服的控制策略．设计了视觉伺服控制器,给出了该控制算法的收敛证明和稳定性分析．通过在轨实施,该策略实现了机械臂/机械手系统拧松螺钉时位姿误差不超过3 mm/2°的任务要求．     

Model Predictive Control for Constrained Image‐Based Visual Servoing in Uncalibrated Environments

This paper presents a novel approach for image‐based visual servoing (IBVS) of a robotic system by considering the constraints in the case when the camera intrinsic and extrinsic parameters are uncalibrated and the position parameters of the features in 3‐D space are unknown. Based on the model predictive control method, the robotic system's input and output constraints, such as visibility constraints and actuators limitations, can be explicitly taken into account. Most of the constrained IBVS controllers use the traditional image Jacobian matrix, the proposed IBVS scheme is developed by using the depth‐independent interaction matrix. The unknown parameters can appear linearly in the prediction model and they can be estimated by the identification algorithm effectively. In addition, the model predictive control determines the optimal control input and updates the estimated parameters together with the prediction model. The proposed approach can simultaneously handle system constraints, unknown camera parameters and depth parameters. Both the visual positioning and tracking tasks can be achieved desired performances. Simulation results based on a 2‐DOF planar robot manipulator for both the eye‐in‐hand and eye‐to‐hand camera configurations are used to demonstrate the effectiveness of the proposed method.