Visual Servoing Path Planning for Cameras Obeying the Unified Model

Abstract

This paper proposes a path planning visual servoing strategy for a class of cameras that includes conventional perspective cameras, fisheye cameras and catadioptric cameras as special cases. Specifically, these cameras are modeled by adopting a unified model recently proposed in the literature and the strategy consists of designing image trajectories for eye-in-hand robotic systems that allow the robot to reach a desired location while satisfying typical visual servoing constraints. To this end, the proposed strategy introduces the projection of the available image features onto a virtual plane and the computation of a feasible image trajectory through polynomial programming. Then, the computed image trajectory is tracked by using an image-based visual servoing controller. Experimental results with a fisheye camera mounted on a 6-d.o.f. robot arm are presented in order to illustrate the proposed strategy.     

Remote Visual Servoing of a Robot Manipulator via Internet2

Visual servoing is a powerful approach to enlarge the applications of robotic systems by incorporating visual information into the control system. On the other hand, teleoperation – the use of machines in a remote way – is increasing the number of applications in many domains. This paper presents a remote visual servoing system using only partial camera calibration and exploiting the high bandwidth of Internet2 to stream video information. The underlying control scheme is based on the image-based philosophy for direct visual servoing – computing the applied torque inputs to the robot based in error signals defined in the image plane – and evoking a velocity field strategy for guidance. The novelty of this paper is a remote visual servoing with the following features: (1) full camera calibration is unnecessary, (2) direct visual servoing does not neglect the robot nonlinear dynamics, and (3) the novel velocity field control approach is utilized. Experiments carried out between two laboratories demonstrated the effectiveness of the application. Work partially supported by CONACyT grant 45826 and CUDI.     

Global Path-Planning for Constrained and Optimal Visual Servoing

Visual servoing consists of steering a robot from an initial to a desired location by exploiting the information provided by visual sensors. This paper deals with the problem of realizing visual servoing for robot manipulators taking into account constraints such as visibility, workspace (that is obstacle avoidance), and joint constraints, while minimizing a cost function such as spanned image area, trajectory length, and curvature. To solve this problem, a new path-planning scheme is proposed. First, a robust object reconstruction is computed from visual measurements which allows one to obtain feasible image trajectories. Second, the rotation path is parameterized through an extension of the Euler parameters that yields an equivalent expression of the rotation matrix as a quadratic function of unconstrained variables, hence, largely simplifying standard parameterizations which involve transcendental functions. Then, polynomials of arbitrary degree are used to complete the parametrization and formulate the desired constraints and costs as a general optimization problem. The optimal trajectory is followed by tracking the image trajectory with an IBVS controller combined with repulsive potential fields in order to fulfill the constraints in real conditions.     

Destination Driven Motion Planning via Obstacle Motion Prediction and Multi-State Path Repair

This paper presents a real-time navigating system named Destination Driven Navigator for a mobile robot operating in unstructured static and dynamic environments. We have designed a new obstacle representation method named Cross-Line Obstacle Representation and a new concept work space to reduce the robot's search space and the environment storage cost, an Adapted Regression Model to predict dynamic obstacles' motion, Multi-State Path Repair rules to quickly translate an infeasible path into feasible one, and the path-planning algorithm to generate a path. A high-level Destination Driven Navigator uses these methods, models and algorithms to guide a mobile robot traveling in various environments while avoiding static and dynamic obstacles. A group of experiments has been conducted. The results exhibit that the Destination Driven Navigator is a powerful and effective paradigm for robot motion planning and obstacle avoidance.     

Adaptive Visual Servoing Using Point and Line Features With an Uncalibrated Eye-in-Hand Camera

This paper presents a novel approach for image-based visual servoing of a robot manipulator with an eye-in-hand camera when the camera parameters are not calibrated and the 3-D coordinates of the features are not known. Both point and line features are considered. This paper extends the concept of depth-independent interaction (or image Jacobian) matrix, developed in earlier work for visual servoing using point features and fixed cameras, to the problem using eye-in-hand cameras and point and line features. By using the depth-independent interaction matrix, it is possible to linearly parameterize, by the unknown camera parameters and the unknown coordinates of the features, the closed-loop dynamics of the system. A new algorithm is developed to estimate unknown parameters online by combining the Slotine–Li method with the idea of structure from motion in computer vision. By minimizing the errors between the real and estimated projections of the feature on multiple images captured during motion of the robot, this new adaptive algorithm can guarantee the convergence of the estimated parameters to the real values up to a scale. On the basis of the nonlinear robot dynamics, we proved asymptotic convergence of the image errors by the Lyapunov theory. Experiments have been conducted to demonstrate the performance of the proposed controller.      

A Modular Scheme for Controller Design and Performance Evaluation in 3D Visual Servoing

In this paper we present a modular scheme for designing and evaluating different control systems for position based dynamic look and move visual servoing systems. This scheme is particularly applied to a 6 DOF industrial manipulator equipped with a camera mounted on its end effector. The manipulator with its actuators and its current feedback loops can be modeled as a Cartesian device commanded through a serial line. In this case the manipulator can be considered as a decoupled system with 6 independent loops. The use of computer vision as feedback transducer strongly affects the closed loop dynamics of the overall system, so that a visual controller is required for achieving fast response and high control accuracy. Due to the long delay in generating the control signal, it is necessary to carefully select the visual controller. In this paper we present a framework that allows the study of some conventional and new techniques to design this visual controller. Besides an experimental setup has been built and used to evaluate and compare the performance of the position based dynamic look and move system with different controllers. Some criterions for selecting the best strategy for each task are established. Quite a lot of results relative to different trajectory tracking control strategies are presented, showing both simulation and real platform responses.     

Selection of Observation Position and Orientation in Visual Servoing with Eye-in-vehicle Configuration for Manipulator

Machine Intelligence Research - In this paper, we propose a method to select the observation position in visual servoing with an eye-in-vehicle configuration for the manipulator. In traditional...     

Path Planning Using Intervals and Graphs

In this paper, the problem of interest is to find a path with given endpoints such that the path lies inside a compact set S given by nonlinear inequalities. The proposed approach uses interval analysis for characterizing S by subpavings (union of boxes) and graph algorithms for finding short feasible paths. As an illustration, the problem of finding collision-free paths for a polygonal rigid object through a space that is cluttered with segment obstacles is considered.     

Fault-tolerant control for uncertain linear systems via adaptive and LMI approaches

This paper proposes a fault-tolerant control scheme for linear systems with mismatched uncertainties which are assumed to be norm-bounded, affine and polytopic, respectively. The linear fractional transformation (LFT) and linear matrix inequality (LMI) techniques are introduced to handle the mismatched uncertainties, and the adaptive techniques are used to compensate actuator faults. By using the cone complementary linearisation algorithm, the resulting stability criteria are converted into solvable ones. Then, on the basis of Lyapunov stability theory, it is shown that the solutions to the closed-loop system and error system are uniformly bounded, especially, the states converge asymptotically to zero. Finally, simulations are given to illustrate the effectiveness and advantages of the proposed theoretical results.     

Real-time Implementation and Validation of a New Hierarchical Path Planning Scheme of UAVs via Hardware-in-the-Loop Simulation

We present a real-time hardware-in-the-loop simulation environment for the validation of a new hierarchical path planning and control algorithm for a small fixed-wing unmanned aerial vehicle (UAV). The complete control algorithm is validated through on-board, real-time implementation on a small autopilot having limited computational resources. We present two distinct real-time software frameworks for implementing the overall control architecture, including path planning, path smoothing, and path following. We emphasize, in particular, the use of a real-time kernel, which is shown to be an effective and robust way to accomplish real-time operation of small UAVs under non-trivial scenarios. By seamless integration of the whole control hierarchy using the real-time kernel, we demonstrate the soundness of the approach. The UAV equipped with a small autopilot, despite its limited computational resources, manages to accomplish sophisticated unsupervised navigation to the target, while autonomously avoiding obstacles.     

Visual Basic中动态报表的设计与实现

VB中如何实现动态报表是一个在开发：VB应用程序时经常碰到的问题，用户要求根据需要选择字段输出不同的报表，本文利用VB的Datareport报表窗体实现了动态报表的输出。     

Visual Basic中动态报表的设计与实现

VB中如何实现动态报表是一个在开发VB应用程序时经常碰到的问题,用户要求根据需要选择字段输出不同的报表,本文利用VB的Datareport报表窗体实现了动态报表的输出。     

Cognitive Mapping and Planning for Visual Navigation

International Journal of Computer Vision - We introduce a neural architecture for navigation in novel environments. Our proposed architecture learns to map from first-person views and plans a...     

移动机器人的路径规划与仿真

在机器人路径优化设计的研究中,由于应用环境存在障碍物,要求寻找最优无碰路径.针对于粒子群优化算法应用于移动机器人路径规划计算中,存在全局搜索能力弱,易出现早熟现象等问题,提出了一种QPSO算法的改进算法.采用8势阱模型的QPSO算法模型简单,控制参数少,全局搜索能力强,但存在早熟收敛的缺陷,从种群的多样性角度分析,在算法的迭代过程中,引入多样性函数,在种群的多样性小于dl.时,由多样性变异操作进行自适应调整,保持了种群中个体的差异性,避免算法陷入局部最优而出现早熟现象.在MATLAB平台上进行仿真,结果表明,改进算法能够有效地解决全局静态无碰路径优化问题,收敛速度、搜索质量与QPSO算法相比明显提高.     

移动机器人的路径规划算法与仿真

研究移动机器人全局路径优化的问题,由于机器人路径随机性强,空间大,存在冗余路径,影响规划速度.传统的进化算法存在着早熟的缺点而得不到最优路径.为了克服传统算法的缺点,提高进化算法的进化速度和精确性,将云理论和粗糙集相结合应用于机器人路径规划,以提高机器人路径规划的效率.仿真由栅格法描述环境随机生成初始路径群,首先利用粗糙集训练得出一系列可行路径的集合,然后利用云进化方法对种群优化,最终得最优行走路线.仿真结果验证改进算法在收敛速度和搜索质量上都有明显的改善.     

实时物流递送路径规划与模拟

近些年来,顾客需求不断多样化、企业竞争更加激烈、全球制造的概念不断发展,不仅我国政府也将物流视为新的经济热点,而且已经引起了全球各个国家的重视。从政府到企业,从中央到地方,都开始物流战略的规划与实施,并且开始物流信息系统的建设。该文以物流路径规划系统为研究对象,介绍了一些著名的最优路径规划算法。在深入分析节约算法的基础上,提出并实现了配合Dijkstra算法的节约里程表算法,开发了以本文算法为核心的实时物流路径规划与模拟系统。     

并行栅格扫描填充路径及其规划算法

深入分析快速成形制件翘曲变形的原因后,提出一种全新的扫描填充路径--并行栅格路径及其规划算法.按照这种路径能够近似、并行地完成整个待成形二维平面区域的扫描填充过程,在减小XY向温度梯度的同时,均匀化不同位置材料成形后的冷却收缩约束力,使得不同位置材料的冷却收缩趋于同步和均匀,减小了制件的整体翘曲变形量.实验表明,该算法能够在与其他类型路径的规划算法大致相当的时间和空间复杂度下,获得扫描填充性能更加优越的路径.     

足球机器人路径规划算法的研究及其仿真

研究足球机器人路径规划优化问题,足球机器人由于赛场情况千变万化,系统本身存在非线性,环境也具有时变性特点,要求机器人相互协作实时性要求高。结合足球机器人系统特点,提出一种蚁群算法的足球机器人路径规划算法。把每一只蚂蚁看作是一个机器人,蚂蚁根据信息素调整自己的前进方向,通过蚂蚁间的信息交流和相互协作快速找到一条最短的机器人运行无碰撞的路径。采用算法进行测试,结果表明,用蚁群算法较好地克服了局部最优的缺陷,获得最优路径,且无碰撞现象,符合足球机器人路径规划的实时性要求。