Velocity planning for a mobile robot to track a moving target — a potential field approach

Potential field method has been widely used for mobile robot path planning, but mostly in a static environment where the target and the obstacles are stationary. The path planning result is normally the direction of the robot motion. In this paper, the potential field method is applied for both path and speed planning, or the velocity planning, for a mobile robot in a dynamic environment where the target and the obstacles are moving. The robot’s planned velocity is determined by relative velocities as well as relative positions among robot, obstacles and targets. The implementation factors such as maximum linear and angular speed of the robot are also considered. The proposed approach guarantees that the robot tracks the moving target while avoiding moving obstacles. Simulation studies are provided to verify the effectiveness of the proposed approach.     

基于线特征与内区域特征的视觉伺服解耦控制

针对多自由度机械臂快速趋近任意四边形态目标的视觉伺服控制难题，提出了结合线特征与内区域特征的机器人视觉伺服解耦控制方法.构建了目标内区域特征以指导相机的平移运动速率，利用目标的线特征给出相机的旋转角速率，并通过引入内区域特征的矢量补偿和质心坐标的位置补偿，实现了平移和旋转控制的部分解耦.最后，对机器人视觉伺服控制系统进行了稳定性分析.仿真验证结果表明所提方法能控制相机以较快而平滑的动作收敛到期望位姿，且在相机光轴与目标平面近似垂直的条件下能较好地克服深度估计造成的不确定性问题.     

On the stabilization of a communication satellite without measuring its angular velocity

The motion control about the center of mass of the communication satellite Yamal-200 is considered. Due to possible failure of the angular velocity sensors, an algorithm for maintaining a prescribed attitude without measuring the angular velocity was developed for this satellite. The algorithm ensures the gyroscopic stabilization of the satellite motion about the local vertical. In the course of control, the onboard computer stores projections of the flywheels?? angular momentum vector on the axes of the inertial basis; the control system tries to preserve the angular momentum magnitude and direction in the inertial space based on the measurements of the angular momentum. The workability of the proposed stabilization algorithm was confirmed by flight tests.     

Path-following control of a mobile robot in the presence of actuator constraints

In this paper, we present a control law for a non-holonomic mobile robot that achieves path following. In the path-following problem, the objective is to control the angular velocity of the robot so that the robot tracks a given reference trajectory. In this paper, we propose a control law that achieves path following in the presence of a constraint on the angular velocity. By applying the proposed control law, the robot can track the reference trajectory even if the distance from the initial position of the robot and the reference trajectory is arbitrary large. Further, we extend the control law so that the linear velocity of the robot becomes small when the robot passes through corners. By using the control algorithm, we can prevent the angular velocity of the robot becoming extremely large when the robot passes through corners. Numerical examples are provided to illustrate the effectiveness of the proposed methods.     

Calculation and correction of attitude parameters without measuring angular velocity

The conventional methods of estimating the parameters of relative attitude of two coordinate trihedrons, a movable trihedron and an immovable one, using representation of vector quantities in projections on the axes of both trihedrons on a finite time interval provide for application of angular velocity of the movable trihedron. This angular velocity is found either by direct measurement or by integration of dynamic equations of angular motion of the solid body correlated with this trihedron. Both ways of calculation of angular velocity have drawbacks. The approach to processing vector information presented below is intended for estimation of the attitude parameters without using any information about the angular velocity of relative motion of the trihedrons. Two problems of determination of attitude of a low-orbit space vehicle are considered as applications.     

激光制导炸弹弹目视线半实物仿真方法的研究

针对风标式导引头测量轴线随遇稳定到制导炸弹相对速度方向上的特点,提出采用等效弹目视线半实物仿真方法来解决三轴飞行无法模拟风标式导引头测量轴线角运动的问题。给出等效弹目视线空间言位的计算方法,讨论了并分析了影响等效弹目视线仿真精度的因素。     

Factor Graph Modeling of Rigid‐body Dynamics for Localization,Mapping, and Parameter Estimation of a Spinning Object in Space

This paper presents a new approach for solving the simultaneous localization and mapping problem for inspecting an unknown and uncooperative object that is spinning about an arbitrary axis in space. This approach probabilistically models the six degree‐of‐freedom rigid‐body dynamics in a factor graph formulation. Using the incremental smoothing and mapping system, this method estimates a feature‐based map of the target object, as well as this object's position, orientation, linear velocity, angular velocity, center of mass, principal axes, and ratios of inertia. This solves an important problem for spacecraft proximity operations. Additionally, it provides a generic framework for incorporating rigid‐body dynamics that may be applied to a number of other terrestrial‐based applications. To evaluate this approach, the Synchronized Position Hold Engage Reorient Experimental Satellites (SPHERES) were used as a testbed within the microgravity environment of the International Space Station. The SPHERES satellites, using body‐mounted stereo cameras, captured a dataset of a target object that was spinning at ten rotations per minute about its unstable, intermediate axis. This dataset was used to experimentally evaluate the approach described in this paper, and it showed that it was able to estimate a geometric map and the position, orientation, linear and angular velocities, center of mass, and ratios of inertia of the target object.     

Conservative differencing procedures for rotationally symmetric flow with swirl

When swirling motion is accompanied by a rapid radial component of flow toward the axis, numerical procedures for handling the coupling term in the azimuthal velocity equation become unstable. The difficulty is averted by replacing this equation with one which governs the angular momentum per unit mass. Moreover, since this is a physically conserved quantity, differencing schemes can be constructed directly from a balance law. Conservative schemes thus emerge automatically.In plane motion of an incompressible fluid, the vorticity is a pseudo-conserved quantity, i.e., it is governed by a differential equation which resembles one derived from a physical balance law. This is not the case for the vorticity of the meridional motion of a rotationally symmetric flow. However, a little known theorem due to the 19th century hydrodynamicist A.F. Svanberg demonstrates that the vorticity divided by the distance from the axis of symmetry is pseudo-conserved. This is useful for deriving differencing schemes governing the meridional motion.In the present paper these concepts are used to obtain prognostic procedures which are then applied to a problem of flow in a crystal-growing crucible. Crystal and crucible rotation provide the swirl and thermocapillary flow provides the inward radial motion which renders earlier procedures unsatisfactory.     

基于多传感器的大口径器件自动对准策略

针对大口径器件的装配, 基于搭建的实验平台, 提出了一种多传感器反馈的分阶段自动对准策略, 实现了大口径器件的六自由度位姿对准. 对准过程中, 在机器人末端远离装配位置时, 采用视觉测量安装框架的相对位姿进行粗对准; 在机器人末端接近装配位置时, 由于安装框架尺寸大导致视觉不能获得完整的框架相对于大口径器件的位姿, 所以采用视觉采集安装框架的局部图像, 利用基于图像的控制消除绕Z轴的旋转误差和沿X、Y轴的平移误差, 采用多个激光测距传感器测量相对距离, 利用基于位置的控制消除沿Z轴的平移误差和绕X、Y轴的旋转误差, 实现大口径器件与安装框架的精对准. 采用增量式PI控制算法, 实现了对准的运动控制. 实验结果验证了所提方法的有效性.     

基于向量场的移动机器人动态路径规划

由于简洁、高效等优点,人工势场法已应用于自主移动机器人的在线实时路径规划,并受到广泛关注.目前,人工势场法在处理静态环境、动态匀速环境下的路径规划方面已有许多成果,但是,机器人在全变速环境下进行在线实时路径规划时,会出现路径冗余、避碰不及等现象.为此,将目标关于机器人的相对加速度因素引入引力势场函数中;在斥力势场函数的基础上融合避碰预测、减速避障策略;最终,机器人能够避免大量无谓避障,当与障碍物相对速度较大时能提前避障,且快速跟踪到目标.仿真结果验证了所提方法的有效性.     

A Stochastic Approach for Blurred Image Restoration and Optical Flow Computation on Field Image Sequence

The blur in target images caused by camera vibration due to robot motion or hand shaking and by object(s) moving in the background scene is different to deal with in the computer vision system.In this paper,the authors study the relation model between motion and blur in the case of object motion existing in video image sequence,and work on a practical computation algorithm for both motion analysis and blut image restoration.Combining the general optical flow and stochastic process,the paper presents and approach by which the motion velocity can be calculated from blurred images.On the other hand,the blurred image can also be restored using the obtained motion information.For solving a problem with small motion limitation on the general optical flow computation,a multiresolution optical flow algoritm based on MAP estimation is proposed. For restoring the blurred image ,an iteration algorithm and the obtained motion velocity are used.The experiment shows that the proposed approach for both motion velocity computation and blurred image restoration works well.     

Motion field and optical flow: qualitative properties

It is shown that the motion field the 2-D vector field which is the perspective projection on the image plane of the 3-D velocity field of a moving scene, and the optical flow, defined as the estimate of the motion field which can be derived from the first-order variation of the image brightness pattern, are in general different, unless special conditions are satisfied. Therefore, dense optical flow is often ill-suited for computing structure from motion and for reconstructing the 3-D velocity field by algorithms which require a locally accurate estimate of the motion field. A different use of the optical flow is suggested. It is shown that the (smoothed) optical flow and the motion field can be interpreted as vector fields tangent to flows of planar dynamical systems. Stable qualitative properties of the motion field, which give useful informations about the 3-D velocity field and the 3-D structure of the scene, usually can be obtained from the optical flow. The idea is supported by results from the theory of structural stability of dynamical systems     

新型移动机器人激光测距雷达的研究

研制了一种新型的基于激光结构光三维视觉技术的移动机器人模块化测距雷达样机,并提出了多平面靶标的转轴现场标定方案,为实现其对周围环境的扫描测量,首先标定线激光器与网络摄像头的相对位置,利用三角法测量激光交线到摄像头光心的距离。然后标定舵机转轴与摄像机的相对位置,并将旋转的激光交线坐标,统一到一个世界坐标系下,实现扫描测距。三维测量实验中,相对误差0.31%,系统测量误差小于4%。实验证明该样机测量精度高,成本低,具有广阔的应用前景。     

Omnidirectional Vision and Inertial Clues for Robot Navigation

The structural features inherent in the visual motion field of a mobile robot contain useful clues about its navigation. The combination of these visual clues and additional inertial sensor information may allow reliable detection of the navigation direction for a mobile robot and also the independent motion that might be present in the 3D scene. The motion field, which is the 2D projection of the 3D scene variations induced by the camera‐robot system, is estimated through optical flow calculations. The singular points of the global optical flow field of omnidirectional image sequences indicate the translational direction of the robot as well as the deviation from its planned path. It is also possible to detect motion patterns of near obstacles or independently moving objects of the scene. In this paper, we introduce the analysis of the intrinsic features of the omnidirectional motion fields, in combination with gyroscopical information, and give some examples of this preliminary analysis. © 2004 Wiley Periodicals, Inc.     

基于单目显微视觉的微球姿态测量方法

微零件的姿态测量对微装配具有重要的作用.但对于微球零件,其姿态的精确测量存在困难,影响了装配精度.针对带有微孔的微球,本文提出了一种基于单目显微视觉的微球姿态高精度测量方法.设计了一种由粗到精的微孔检测算法,实现了高精度的微孔定位.通过对相机光轴方向的标定,在相机运动后对微球图像坐标进行补偿,提高了在相机坐标系下的微球定位精度.通过对微球和微孔的精确定位,计算出微球球心与微孔圆心的空间相对位置,实现了相机坐标系下高精度的微球姿态测量.同时,根据标定出的相机坐标系与调整平台坐标系之间的旋转关系,将微球姿态转换到调整平台坐标系.实验结果表明,最大姿态测量误差0.3度,验证了本文方法的有效性.     

基于点云的补漆机器人系统

汽车补漆机器人需要面对各种不同大小的车型,适配各种造型曲面和颜色,这种高度自适应要求使得补漆机器人在目标跟踪、路径规划、运动空间等方面的设计难度远超汽车厂的喷漆机器人.因此需要重新规划喷漆路径,首先对汽车的点云数据进行分部位切割,然后以八邻域法计算封闭曲面轮廓,最后以切片法在曲面上生成光栅轨迹,形成了每一个补漆面的关键路径.设计了八轴桁架机器人系统,用蚁群算法计算生成八轴联动时的路径规划,再通过倍福的ADS协议将路径数据和梯形曲线的加速度下发到PLC运动控制程序,完成各关节轴的联动协同补漆运动.实测表明,该系统能针对不同汽车,自动控制机器人工具轴心以法向量对准任意曲面,并以联动方式驱动八轴平稳跟踪曲面运动.该系统可广泛应用于各种曲面的机器人加工.     

Zoom tracking and its applications

We present a new active vision technique called zoom tracking. Zoom tracking is the continuous adjustment of a camera's focal length in order to keep a constant-sized image of an object moving along the camera's optical axis. Two methods for performing zoom tracking are presented: a closed-loop visual feedback algorithm based on optical flow, and use of depth information obtained from an autofocus camera's range sensor. We explore two uses of zoom tracking: recovery of depth information and improving the performance of scale-variant algorithms. We show that the image stability provided by zoom tracking improves the performance of algorithms that are scale variant, such as correlation-based trackers. While zoom tracking cannot totally compensate for an object's motion, due to the effect of perspective distortion, an analysis of this distortion provides a quantitative estimate of the performance of zoom tracking. Zoom tracking can be used to reconstruct a depth map of the tracked object. We show that under normal circumstances this reconstruction is much more accurate than depth from zooming, and works over a greater range than depth from axial motion while providing, in the worst case, only slightly less accurate results. Finally, we show how zoom tracking can also be used in time-to-contact calculations. Received: 15 February 2000 / Accepted: 19 June 2000     

Stabilization of a 3D axially symmetric pendulum

Stabilizing controllers are developed for a 3D pendulum assuming that the pendulum has a single axis of symmetry and that the center of mass lies on the axis of symmetry. This assumption allows development of a reduced model that forms the basis for controller design and global closed-loop analysis; this reduced model is parameterized by the constant angular velocity component of the 3D pendulum about its axis of symmetry. Several different controllers are proposed. Controllers based on angular velocity feedback only, asymptotically stabilize the hanging equilibrium. Then controllers are introduced, based on angular velocity and reduced attitude feedback, that asymptotically stabilize either the hanging equilibrium or the inverted equilibrium. These problems can be viewed as stabilization of a Lagrange top. Finally, if the angular velocity about the axis of symmetry is assumed to be zero, controllers are introduced, based on angular velocity and reduced attitude feedback, that asymptotically stabilize either the hanging equilibrium or the inverted equilibrium. This problem can be viewed as stabilization of a spherical pendulum.     

Sensor Fusion for Joint Kinematic Estimation in Serial Robots Using Encoder,Accelerometer and Gyroscope

Open-chain manipulator robots play an important role in the industry, since they are utilized in applications requiring precise motion. High-performance motion of a robot system mainly relies on adequate trajectory planning and the controller that coordinates the movement. The controller performance depends of both, the employed control law and the sensor feedback. Optical encoder feedback is the most used sensor for angular position estimation of each joint in the robot, since they feature accurate and low noise angular position measurements. However, it cannot detect mechanical imperfections and deformations common in open chain robots. Moreover, velocity and acceleration cannot be extracted from the encoder data without adding phase delays. Sensor fusion techniques are found to be a good solution for solving this problem. However, few works has been carried out in serial robots for kinematic estimation of angular position, velocity and acceleration, since the delays induced by the filtering techniques avoids its use as controller feedback. This work proposes a novel sensor-fusion-based feedback system capable of providing complete kinematic information from each joint in 4-degrees of freedom serial robot, with the contribution of a proposed methodology based on Kalman filtering for fusing the information from optical encoder, gyroscope and accelerometer appended to the robot. Calibration and experimentation are carried out for validating the proposal. The results are compared with another kinematic estimation technique finding that this proposal provides more information about the robot movement without adding state delays, which is important for being used as controller feedback.     

Autonomous mobile robot dynamic motion planning using hybrid fuzzy potential field

A new fuzzy-based potential field method is presented in this paper for autonomous mobile robot motion planning with dynamic environments including static or moving target and obstacles. Two fuzzy Mamdani and TSK models have been used to develop the total attractive and repulsive forces acting on the mobile robot. The attractive and repulsive forces were estimated using four inputs representing the relative position and velocity between the target and the robot in the x and y directions, in one hand, and between the obstacle and the robot, on the other hand. The proposed fuzzy potential field motion planning was investigated based on several conducted MATLAB simulation scenarios for robot motion planning within realistic dynamic environments. As it was noticed from these simulations that the proposed approach was able to provide the robot with collision-free path to softly land on the moving target and solve the local minimum problem within any stationary or dynamic environment compared to other potential field-based approaches.