(PPI).PPI's localization library utilizes a multisensor fusion approachfor real-time vehicle localization in structured environments such as underground parking lots. PPI's algorithm integrates the onboard motion sensors, a set of mid-range automotive radars, and two-dimensional(2D) high definition(...
In this paper, we address the robust LiDAR localization problem of multi-source fusion in complex dynamic autonomous driving environments. We design a tightly-coupled LiDAR-IMU-GNSS localization framework with moving object segmentation, including data pre-processing, front-end odometry estimation, and ...
Multisensor Fusion for Localization and Mapping This project aims to provide a open-sourced framework for multisensor fusion in localization and mapping. Install the following dependencies to run this project: ROS g2o GeographlicLib glog PCL protobuf sophus YAML Dataset This is a modified kitti ...
原文连接:[1711.05805v1] Robust and Precise Vehicle Localization based on Multi-sensor Fusion in Diverse City Scenes (arxiv.org) 基于多传感器融合的车辆在不同城市场景下鲁棒精确定位 摘要 我们提出了一个鲁棒和精确的定位系统,实现厘米级的定位精度在不同的城市场景。我们的系统自适应地使用来自互补传感器(如...
Localization of the Wheeled Mobile Robot Based on Multi-Sensor Data Fusion The paper presents a method of localization of a mobile robot which relies on aggregation of data from several sensors. A review of the state of the art re... P Jaroszek,M Trojnacki 被引量: 7发表: 2015年 Workspa...
Simultaneous Localization and Mapping (SLAM) is the foundation for high-precision localization, environmental awareness, and autonomous decision-making of autonomous vehicles. It has developed rapidly, but there are still challenges such as sensor errors, data fusion, and real-time computing. This paper...
《Robust and Precise Vehicle Localization based on Multi-sensor Fusionin Diverse City Scenes》翻译,车辆定位是自动驾驶的基本任务之一。由于卫星轨道和时钟误差,加上对流层和电离层延迟,全球导航卫星系统(GNSS)的单点定位精度约为10米。这些误差可以用测量的参考站
Keywords:datafusion;symmetricalperturbationmodel;CC automaticcalibration;polynomial environmentalmap;robotlocalization 将环境模型用多边形地图建模,然后用重构 的地图与环境模型进行匹配,假设机器人配备的 传感器无噪声并且所获得的信息绝对精确,这时 将机器人定位问题分成两项 [ 1 ] :假设产生项和假 设清除项 [ 2 ]...
In order to solve the problem that the standard extended Kalman filter (EKF) algorithm has large errors in Unmanned Aerial Vehicle (UAV) multi-sensor fusion localization, this paper proposes a multi-sensor fusion localization method based on adaptive error correction EKF algorithm. Firstly, a multi...
In particular, algorithms able to accommodate sensor fusion techniques enable increased accuracy, and are more resilient against the malfunction of individual sensors. The development of algorithms for autonomous navigation, mapping and localization have seen big advancements over the past two decades. ...