在未知环境中进行半自主导航的人为干预的自我中心界面

Mehul Gupta, Larry Guy, Sahil Mithani, Avanish Narumanchi, Barry Walker, Shiyu Feng, P. Vela
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引用次数: 0

摘要

在未知环境中进行半自主导航是机器人研究的一个重要领域,在搜索和救援、环境监测和勘探等领域具有许多潜在的应用。然而,现有的方法依赖于机器人已经有一个半精确的环境地图,在一个陌生的环境中不能假设是真实的。为了解决这个问题,本研究论文提出了一个新的以自我为中心的界面,它提供了一个基于机器人操作系统(ROS)的软件,利用机器人的相机视图。通过这个接口,操作员可以在机器人的相机视图中选择一个可见的点,并将其作为机器人局部环境中的中间目标。利用机器人系统固有的路径规划和导航工具,推导出机器人的无碰撞路径。当机器人沿着给定的路径移动时,操作员可以继续提供中间目标,并根据最近的观察调整其路径。这个过程是通过Gazebo模拟器模拟的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Ego-Centric Interface for Human Intervention in Semi-Autonomous Navigation through Unknown Environments
Semi-autonomous navigation through unknown environments is an important area of research for robotics, with many potential applications in fields such as search and rescue, environmental monitoring, and exploration. However, existing methods rely on the robot to already have a semi-accurate map of the environment which cannot be assumed to be true in an unfamiliar environment. To address this, a new egocentric interface has been presented in this research paper, which provides a Robot Operating System (ROS)-based software utilizing the robot’s camera view. With this interface, a human operator can select a point visible in the robot’s camera view and provide it as an intermediate goal in the robot’s local environment. Using the robotic system’s inherent path-planning and navigation tools, a collision-free path is derived for the robot to follow. While the robot moves along the given path, a human operator may continue to provide intermediate goals and adjust its path based on recent observations. This process is simulated through the Gazebo simulator.
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