论文标题
在未知障碍物环境中的在线探索和覆盖计划
Online Exploration and Coverage Planning in Unknown Obstacle-Cluttered Environments
论文作者
论文摘要
在线覆盖计划在现场监控，搜索和救援等应用程序中可能很有用。没有事先的环境信息，考虑到普遍使用的车辆（例如，车轮机器人）的非独立迁移率限制，实现决议完全覆盖范围仍然是一个挑战。在本文中，我们建议针对未知的，障碍物整洁的环境的基于十六进制的覆盖范围计划算法。提出的方法可确保分辨率完全覆盖范围，可以调整以实现快速探索，并计划平稳的道路，使Dubins车辆实时以恒定的速度遵循。凉亭模拟和硬件实验具有非全面轮式机器人的表明，我们的方法可以在覆盖范围和勘探速度之间成功折衷，并且根据总覆盖区域或勘探速度，根据其调整方式，可以超越现有的在线覆盖算法。
Online coverage planning can be useful in applications like field monitoring and search and rescue. Without prior information of the environment, achieving resolution-complete coverage considering the non-holonomic mobility constraints in commonly-used vehicles (e.g., wheeled robots) remains a challenge. In this paper, we propose a hierarchical, hex-decomposition-based coverage planning algorithm for unknown, obstacle-cluttered environments. The proposed approach ensures resolution-complete coverage, can be tuned to achieve fast exploration, and plans smooth paths for Dubins vehicles to follow at constant velocity in real-time. Gazebo simulations and hardware experiments with a non-holonomic wheeled robot show that our approach can successfully tradeoff between coverage and exploration speed and can outperform existing online coverage algorithms in terms of total covered area or exploration speed according to how it is tuned.
