This article establishes the Exploration-RRT algorithm: A novel general-purpose combined exploration and pathplanning algorithm, based on a multi-goal Rapidly-Exploring Random Trees (RRT) framework. Exploration-RRT (ERRT) has been specifically designed for utilization in 3D exploration missions, with partially or completely unknown and unstructured environments. The novel proposed ERRT is based on a multi-objective optimization framework and it is able to take under consideration the potential information gain, the distance travelled, and the actuation costs, along trajectories to pseudo-random goals, generated from considering the on-board sensor model and the non-linear model of the utilized platform. In this article, the algorithmic pipeline of the ERRT will be established and the overall applicability and efficiency of the proposed scheme will be presented on an application with an Unmanned Aerial Vehicle (UAV) model, equipped with a 3D lidar, in a simulated operating environment, with the goal of exploring a completely unknown area as efficiently and quickly as possible

翻译：本条确立了勘探-RRT算法:一种基于多目标快速勘探随机树(RRT)框架的新型通用综合勘探和路径规划算法。勘探-RRT(ERRT)是专门设计用于3D勘探飞行任务的,其环境是部分或全部未知的,没有结构的环境是部分或全部的。拟议的新的ERRT基于一个多目标优化框架,它能够考虑到在模拟操作环境中可能获得的信息、行走的距离、与假随机目标的轨迹有关的演动成本以及从考虑机载传感器模型和已使用平台的非线性模型中生成的假随机目标的轨迹轨迹。在本篇文章中,将确定ERRT的逻辑管道,并将在一项应用中介绍拟议计划的总体适用性和效率,该应用中将配备一个配备3Dlidar的无人驾驶飞行器模型,在模拟操作环境中安装3Dlidar,目的是尽可能高效和快速探索一个完全未知的区域。