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基于地面可通行性的连续分类的自然环境下的反应式导航

Reactive Navigation on Natural Environments by Continuous Classification of Ground Traversability.

机构信息

Robotics and Mechatronic Lab, Andalucía Tech, Universidad de Málaga, 29071 Málaga, Spain.

出版信息

Sensors (Basel). 2020 Nov 10;20(22):6423. doi: 10.3390/s20226423.

DOI:10.3390/s20226423
PMID:33182808
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7697802/
Abstract

Reactivity is a key component for autonomous vehicles navigating on natural terrains in order to safely avoid unknown obstacles. To this end, it is necessary to continuously assess traversability by processing on-board sensor data. This paper describes the case study of mobile robot Andabata that classifies traversable points from 3D laser scans acquired in motion of its vicinity to build 2D local traversability maps. Realistic robotic simulations with Gazebo were employed to appropriately adjust reactive behaviors. As a result, successful navigation tests with Andabata using the robot operating system (ROS) were performed on natural environments at low speeds.

摘要

机器人安德巴塔（Andabata）在自然环境中以低速进行自主导航时，需要对周围环境进行感知，从而安全地避开未知障碍物。为了实现这一目标，它需要通过处理 onboard 传感器数据来实时评估地形的可通行性。本文描述了一个案例研究，即通过对机器人运动过程中附近的 3D 激光扫描数据进行处理，将可通行区域分类，从而构建 2D 局部可通行地图。该研究使用 Gazebo 进行了逼真的机器人仿真，以适当调整机器人的反应行为。结果，在自然环境中，机器人安德巴塔（Andabata）成功地使用机器人操作系统（ROS）以低速进行了导航测试。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/792b/7697802/a09c6744e0cc/sensors-20-06423-g020.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/792b/7697802/88b2538f8b86/sensors-20-06423-g010.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/792b/7697802/4b91d4a5d8bf/sensors-20-06423-g012.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/792b/7697802/d00c8abed6af/sensors-20-06423-g016.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/792b/7697802/4e2d16c55c41/sensors-20-06423-g017.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/792b/7697802/dc764527c1b1/sensors-20-06423-g018.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/792b/7697802/a09c6744e0cc/sensors-20-06423-g020.jpg

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Traversability Assessment and Trajectory Planning of Unmanned Ground Vehicles with Suspension Systems on Rough Terrain.崎岖地形下带悬架系统的无人地面车辆的可行驶性评估与轨迹规划。
Sensors (Basel). 2019 Oct 10;19(20):4372. doi: 10.3390/s19204372.
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Adaptive Obstacle Detection for Mobile Robots in Urban Environments Using Downward-Looking 2D LiDAR.
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Sensors (Basel). 2022 Jul 26;22(15):5599. doi: 10.3390/s22155599.
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A Dynamic Motion Analysis of a Six-Wheel Ground Vehicle for Emergency Intervention Actions.六轮地面应急干预车辆的动态运动分析
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使用下视二维激光雷达的城市环境中移动机器人自适应障碍物检测
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