• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Journal of Robotic Systems >Flying on point clouds: Online trajectory generation and autonomous navigation for quadrotors in cluttered environments
【24h】

Flying on point clouds: Online trajectory generation and autonomous navigation for quadrotors in cluttered environments

机译：飞行点云：在杂乱环境中的标准运动员的在线轨迹生成和自主导航

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Micro aerial vehicles (MAVs), especially quadrotors, have been widely used in field applications, such as disaster response, field surveillance, and search-and-rescue. For accomplishing such missions in challenging environments, the capability of navigating with full autonomy while avoiding unexpected obstacles is the most crucial requirement. In this paper, we present a framework for online generating safe and dynamically feasible trajectories directly on the point cloud, which is the lowest-level representation of range measurements and is applicable to different sensor types. We develop a quadrotor platform equipped with a three-dimensional (3D) light detection and ranging (LiDAR) and an inertial measurement unit (IMU) for simultaneously estimating states of the vehicle and building point cloud maps of the environment. Based on the incrementally registered point clouds, we online generate and refine a flight corridor, which represents the free space that the trajectory of the quadrotor should lie in. We represent the trajectory as piecewise Bezier curves by using the Bernstein polynomial basis and formulate the trajectory generation problem as a convex program. By using Bezier curves, we can constrain the position and kinodynamics of the trajectory entirely within the flight corridor and given physical limits. The proposed approach is implemented to run onboard in real-time and is integrated into an autonomous quadrotor platform. We demonstrate fully autonomous quadrotor flights in unknown, complex environments to validate the proposed method.
机译：微空中车辆（MAV），尤其是四分波，已广泛用于现场应用，例如灾害响应，现场监控和救援。为了在挑战环境中实现这样的任务，在避免意外障碍的同时导航的能力是最关键的要求。在本文中，我们提出了一种在线生成安全和动态可行的轨迹的框架，直接在点云上，这是范围测量的最低级别表示，并且适用于不同的传感器类型。我们开发一个配备有三维（3D）光检测和测距（LIDAR）和惯性测量单元（IMU）的四轨平台，用于同时估计车辆的状态和建筑点云图的状态。基于逐步注册的点云，我们在线生成和改进飞行走廊，这代表了四射轮轨迹应该躺在的自由空间。我们通过使用伯尔尼斯坦多项式基础作为分段Bezier曲线来表示轨迹并制定轨迹生成问题作为凸面编程。通过使用Bezier曲线，我们可以完全在飞行走廊内限制轨迹的位置和血管动力学和给予物理限制。所提出的方法是实时运行的，并将其集成到自动正音频平台中。我们展示了在未知，复杂的环境中的完全自主的四轮机器航班，以验证所提出的方法。

著录项

  • 来源
    《Journal of Robotic Systems》 |2019年第4期|710-733|共24页
  • 作者

    Gao Fei; Wu William; Gao Wenliang; Shen Shaojie;

  • 作者单位

    Hong Kong Univ Sci & Technol Robot Inst Dept Elect & Comp Engn Clear Water Bay Hong Kong Peoples R China;

    Hong Kong Univ Sci & Technol Robot Inst Dept Elect & Comp Engn Clear Water Bay Hong Kong Peoples R China;

    Hong Kong Univ Sci & Technol Robot Inst Dept Elect & Comp Engn Clear Water Bay Hong Kong Peoples R China;

    Hong Kong Univ Sci & Technol Robot Inst Dept Elect & Comp Engn Clear Water Bay Hong Kong Peoples R China;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    aerial robotics; autonomous navigation; motion planning; trajectory generation;

    机译：空中机器人;自主导航;运动规划;轨迹代;

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号