This work establishes COMPRA, a compact and reactive autonomy framework for fast deployment of Micro Aerial Vehicles (MAVs) in subterranean Search-and-Rescue (SAR) missions. A COMPRA-enabled MAV is able to autonomously explore previously unknown areas while specific mission criteria are considered e.g. an object of interest is identified and localized, the remaining useful battery life, the overall desired exploration mission duration. The proposed architecture follows a low-complexity algorithmic design to facilitate fully on-board computations, including nonlinear control, state-estimation, navigation, exploration behavior and object localization capabilities. The framework is mainly structured around a reactive local avoidance planner, based on enhanced Potential Field concepts and using instantaneous 3D pointclouds, as well as a computationally efficient heading regulation technique, based on depth images from an instantaneous camera stream. Those techniques decouple the collision-free path generation from the dependency of a global map and are capable of handling imprecise localization occasions. Field experimental verification of the overall architecture is performed in relevant unknown Global Positioning System (GPS)-denied environments.
翻译:这项工作为快速部署小型航空车辆(MAVs)在地下搜索和救援(SAR)任务中的快速部署,建立了COMPRA,这是一个紧凑和被动的自主框架;一个由COMRA支持的MAV能够自主地探索以前未知的区域,同时考虑具体的特派团标准,例如确定一个感兴趣的对象,确定一个地方,确定剩余的有用电池寿命,整个勘探任务期限;拟议的结构采用低兼容性算法设计,以便利在船上进行充分计算,包括非线性控制、国家估计、导航、探索行为和物体定位能力;该框架主要围绕一个反应性的当地避险规划器,以强化的外地概念为基础,使用瞬时3D点焦云,以及一个基于瞬时照相机流深度图像的计算效率高的标题管理技术;这些技术使无碰撞路径生成与全球地图依赖性脱钩,能够处理不精确的本地化情况;总体结构的实地试验性核查是在相关未知的全球定位系统(GPPS)封闭环境中进行的。