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Mobile Robot Navigation for Person Following in Indoor Environments.

机译:在室内环境中针对跟随人员的移动机器人导航。

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摘要

Service robotics is a rapidly growing area of interest in robotics research. Service robots inhabit human-populated environments and carry out specific tasks. The goal of this dissertation is to develop a service robot capable of following a human leader around populated indoor environments. A classification system for person followers is proposed such that it clearly defines the expected interaction between the leader and the robotic follower. In populated environments, the robot needs to be able to detect and identify its leader and track the leader through occlusions, a common characteristic of populated spaces. An appearance-based person descriptor, which augments the Kinect skeletal tracker, is developed and its performance in detecting and overcoming short and long-term leader occlusions is demonstrated. While following its leader, the robot has to ensure that it does not collide with stationary and moving obstacles, including other humans, in the environment. This requirement necessitates the use of a systematic navigation algorithm. A modified version of navigation function path planning, called the predictive fields path planner, is developed. This path planner models the motion of obstacles, uses a simplified representation of practical workspaces, and generates bounded, stable control inputs which guide the robot to its desired position without collisions with obstacles. The predictive fields path planner is experimentally verified on a non-person follower system and then integrated into the robot navigation module of the person follower system. To navigate the robot, it is necessary to localize it within its environment. A mapping approach based on depth data from the Kinect RGB-D sensor is used in generating a local map of the environment. The map is generated by combining inter-frame rotation and translation estimates based on scan generation and dead reckoning respectively. Thus, a complete mobile robot navigation system for person following in indoor environments is presented.
机译:服务机器人技术是机器人研究领域中一个快速增长的兴趣领域。服务机器人居住在人口稠密的环境中并执行特定任务。本文的目的是开发一种服务机器人,该机器人能够跟随人口稠密的室内环境中的人类领导者。提出了针对人员跟随者的分类系统,以使其明确定义领导者与机器人关注者之间的预期交互。在人口稠密的环境中,机器人需要能够检测和识别其领导者,并通过遮挡物来跟踪领导者,遮挡物是居住空间的共同特征。基于外观的人描述符可以增强Kinect骨骼跟踪器,并可以证明其在检测和克服短期和长期领导者遮挡方面的性能。在跟随其领导者时,机器人必须确保其不会与环境中的静止和移动障碍物(包括其他人)相撞。该要求需要使用系统的导航算法。开发了导航功能路径规划的修改版本,称为预测字段路径规划器。该路径规划器对障碍物的运动进行建模,使用实际工作空间的简化表示,并生成有边界的稳定控制输入,这些输入将机器人引导至所需位置而不会与障碍物发生碰撞。预测性领域路径规划器在非人员追踪器系统上进行了实验验证,然后集成到人员追踪器系统的机器人导航模块中。要导航机器人,必须在其环境中对其进行本地化。基于来自Kinect RGB-D传感器的深度数据的映射方法用于生成环境的局部图。通过分别基于扫描生成和航位推算组合帧间旋转和平移估计来生成地图。因此,提出了一种用于室内环境中的人员跟踪的完整的移动机器人导航系统。

著录项

  • 作者

    Pradhan, Ninad.;

  • 作者单位

    Clemson University.;

  • 授予单位 Clemson University.;
  • 学科 Engineering Computer.;Engineering Robotics.;Engineering Electronics and Electrical.
  • 学位 Ph.D.
  • 年度 2013
  • 页码 177 p.
  • 总页数 177
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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