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Multisensor based environment modelling and control applications for mobile robots.

机译：基于多传感器的移动机器人环境建模和控制应用程序。

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摘要

For autonomous operations of mobile robots, three key functionalities are required: (a) knowledge of the structure of the world in which it operates, (b) ability to navigate to different positions autonomously using path planning algorithms, and (c) ability to precisely localize itself for the task execution. This thesis will address some of the issues related to the first and third requirements. The knowledge of the structure of the environment can be represented in several forms such as: 3D models, 2D wall plan, 2D plan of landmarks, and position and velocity of moving objects. Efficient navigation and obstacle avoidance methods are often aided by information about the structure of the environment in any of the above forms. At the end of each navigation task the robot has to execute an assigned task such as pick and place or park. In most cases these tasks require precise localization of the robot where the degree of precision required depends on the task specification.;Taking these functions into consideration, this thesis addresses the issues of learning the structure of the world by constructing a visual landmark map of static landmarks. Additionally, it provides a solution to the precise localization problem of the mobile robot using a vision based hybrid controller. On the subject of the visual landmark map, the thesis describes a landmark position measurement system using an integrated laser-camera sensor. The traditional laser range finder can be used to detect landmarks that are direction invariant in the laser data. The processes that are dependent on the presence of directional invariant features such as navigation and simultaneous localization and mapping (SLAM) algorithms will fail to function in their absence. However, in many instances, it is possible to find a larger number of landmarks that are visually salient using computer vision. The calculation of depth to a visual feature is non-trivial due to the loss of depth information in the sensor model. While considering the drawbacks and limitations in laser and camera as a sensor, this thesis proposes a novel integrated sensor method to calculate position of the visual features. In addition, a comprehensive experimental analysis is presented to verify the sensor integration method for the EKF based SLAM algorithm. For effective operation of a robot's SLAM algorithm, it is necessary to identify dynamic objects in the environment. In order to achieve this objective a novel robust technique for detecting moving objects using a laser ranger mounted on a mobile robot is presented. After initial alignment of two consecutive laser scans, each laser reading is segmented and classified according to object type: stationary, non-stationary or indeterminate. Laser reading segments are then analyzed using an algorithm to maximally recover the moving objects. The proposed algorithm has the ability to recover all possible laser readings that belong to moving objects. The developed algorithm is verified using experimental results in which a walking person is detected by a moving robot.;Finally, a novel vision-based hybrid controller for parking of mobile robots is proposed. Parking or docking is an essential behavioral unit for autonomous robots. The proposed hybrid controller is comprised of a discrete event controller to change the direction of travel and a pixel error driven proportional controller to generate motion commands to achieve the continuous motion. At the velocity control level, the robot is driven using a built-in PID control system. The feedback system uses image plane measurements in pixel units to perform image-based visual servoing (IBVS). The constraints imposed due to the nonholonomic nature of the robot and the limited field of view of the camera are taken into account in designing the IBVS-based controller. The controller continuously compares the current view of the parking station against the reference view until the desired parking condition is achieved. A comprehensive analysis is provided to prove the convergence of the proposed method. Once the proposed parking behaviour is invoked, the robot has the ability to start from any arbitrary position to achieve successful parking given that initially the parking station is in the robot's field of view. As the method is purely based on vision the hybrid controller does not require any position information (or localization) of the robot. Using a Pioneer 3AT robot, several experiments are carried out to validate the method. The experimental system has the ability to achieve the parking state and align laterally within 1 cm of the target pose.
机译：对于移动机器人的自主操作，需要三个关键功能：（a）了解其运行所在的世界的结构，（b）使用路径规划算法自主导航到不同位置的能力，以及（c）精确定位的能力本地化以执行任务。本论文将解决与第一和第三要求有关的一些问题。对环境结构的了解可以用几种形式表示，例如：3D模型，2D墙平面图，地标2D平面图以及移动物体的位置和速度。通常以上述任何形式的有关环境结构的信息都有助于有效的导航和避障方法。在每个导航任务结束时，机器人必须执行分配的任务，例如拾取和放置或停放。在大多数情况下，这些任务需要对机器人进行精确定位，而精确度取决于任务规范。；考虑到这些功能，本论文通过构建静态的视觉界标图来解决学习世界结构的问题地标。此外，它使用基于视觉的混合控制器为移动机器人的精确定位问题提供了解决方案。在视觉界标地图的主题上，论文描述了使用集成激光相机传感器的界标位置测量系统。传统的激光测距仪可用于检测激光数据中方向不变的界标。依赖于方向不变特征（例如导航，同时定位和映射（SLAM）算法）的存在的过程在没有它们的情况下将无法运行。但是，在许多情况下，有可能找到大量使用计算机视觉在视觉上显着的地标。由于传感器模型中深度信息的丢失，因此视觉特征深度的计算是不平凡的。在考虑激光和照相机作为传感器的弊端和局限性的同时，提出了一种新颖的综合传感器方法来计算视觉特征的位置。此外，进行了全面的实验分析，以验证基于EKF的SLAM算法的传感器集成方法。为了使机器人的SLAM算法有效运行，有必要识别环境中的动态对象。为了实现该目的，提出了一种新颖的鲁棒技术，该技术使用安装在移动机器人上的激光测距仪来检测运动对象。初始对准两个连续的激光扫描后，将根据对象类型对每个激光读数进行分段和分类：固定，非固定或不确定。然后使用一种算法分析激光读取段，以最大程度地恢复运动对象。所提出的算法具有恢复属于移动物体的所有可能的激光读数的能力。实验结果验证了该算法的有效性。实验结果表明运动机器人能够检测到步行者。最后，提出了一种新型的基于视觉的移动机器人停车混合控制器。停车或对接是自主机器人的基本行为单元。提出的混合控制器包括一个用于改变行进方向的离散事件控制器和一个用于驱动连续运动的运动命令的像素误差驱动比例控制器。在速度控制级别，使用内置的PID控制系统驱动机器人。反馈系统使用以像素为单位的图像平面测量值来执行基于图像的视觉伺服（IBVS）。在设计基于IBVS的控制器时，要考虑到由于机器人的非完整特性和摄像机的有限视野而施加的约束。控制器不断将停车位的当前视图与参考视图进行比较，直到获得所需的停车条件为止。提供了全面的分析以证明所提出方法的收敛性。一旦提出了建议的停车行为，假设停车位最初在机器人的视野内，则机器人可以从任意位置启动以成功停车。由于该方法仅基于视觉，因此混合控制器不需要机器人的任何位置信息（或定位）。使用Pioneer 3AT机器人，进行了多次实验以验证该方法。实验系统具有实现驻车状态并在目标姿势的1 cm之内横向对齐的能力。

著录项

  • 作者

    Amarasinghe, Dilan.;

  • 作者单位

    Memorial University of Newfoundland (Canada).;

  • 授予单位 Memorial University of Newfoundland (Canada).;
  • 学科 Engineering Electronics and Electrical.;Engineering Robotics.
  • 学位 Ph.D.
  • 年度 2008
  • 页码 160 p.
  • 总页数 160
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 无线电电子学、电信技术;
  • 关键词

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