Related papers: Tightly-Coupled, Speed-aided Monocular Visual-Iner…
Localization is paramount for autonomous robots. While camera and LiDAR-based approaches have been extensively investigated, they are affected by adverse illumination and weather conditions. Therefore, radar sensors have recently gained…
In this paper, we propose an novel implementation of a simultaneous localization and mapping (SLAM) system based on a monocular camera from an unmanned aerial vehicle (UAV) using Depth prediction performed with Capsule Networks (CapsNet),…
Cross-modal localization has drawn increasing attention in recent years, while the visual relocalization in prior LiDAR maps is less studied. Related methods usually suffer from inconsistency between the 2D texture and 3D geometry,…
This paper presents a novel tightly coupled Filter-based monocular visual-inertial-wheel odometry (VIWO) system for ground robots, designed to deliver accurate and robust localization in long-term complex outdoor navigation scenarios. As an…
An automated vehicle operating in an urban environment must be able to perceive and recognise object/obstacles in a three-dimensional world while navigating in a constantly changing environment. In order to plan and execute accurate…
Advancements in LiDAR technology have led to more cost-effective production while simultaneously improving precision and resolution. As a result, LiDAR has become integral to vehicle localization, achieving centimeter-level accuracy through…
A reliable sense-and-avoid system is critical to enabling safe autonomous operation of unmanned aircraft. Existing sense-and-avoid methods often require specialized sensors that are too large or power intensive for use on small unmanned…
Vehicle localization in highway tunnels is a challenging issue for autonomous vehicle navigation. Since GPS signals from satellites cannot be received inside a highway tunnel, map-aided localization is essential. However, the environment…
Accurate vehicle localization is a crucial step towards building effective Vehicle-to-Vehicle networks and automotive applications. Yet standard grade GPS data, such as that provided by mobile phones, is often noisy and exhibits significant…
Fiducial markers can encode rich information about the environment and can aid Visual SLAM (VSLAM) approaches in reconstructing maps with practical semantic information. Current marker-based VSLAM approaches mainly utilize markers for…
Fast pose estimation (PE) is of vital importance for successful mission performance of agile autonomous robots. Global Positioning Systems such as GPS and GNSS have been typically used in fusion with Inertial Navigation Systems (INS) for…
An algorithm for pose and motion estimation using corresponding features in images and a digital terrain map is proposed. Using a Digital Terrain (or Digital Elevation) Map (DTM/DEM) as a global reference enables recovering the absolute…
A novel relative localization approach for guidance of a micro-scale Unmanned Aerial Vehicle (UAV) by a well-equipped aerial robot fusing Visual-Inertial Odometry (VIO) with Light Detection and Ranging (LiDAR) is proposed in this paper.…
Fine localization is a crucial task for autonomous vehicles. Although many algorithms have been explored in the literature for this specific task, the goal of getting accurate results from commodity sensors remains a challenge. As…
This paper develops a stop line aided cooperative positioning framework for connected vehicles, which creatively utilizes the location of the stop-line to achieve the positioning enhancement for a vehicular ad-hoc network (VANET) in…
In this paper, a robust vehicle local position estimation with the help of single camera sensor and GPS is presented. A modified Inverse Perspective Mapping, illuminant Invariant techniques and object detection based approach is used to…
Modern robotic systems are required to operate in challenging environments, which demand reliable localization under challenging conditions. LiDAR-based localization methods, such as the Iterative Closest Point (ICP) algorithm, can suffer…
We present TOPGN, a novel method for real-time transparent obstacle detection for robot navigation in unknown environments. We use a multi-layer 2D grid map representation obtained by summing the intensities of lidar point clouds that lie…
Visual localization on standard-definition (SD) maps has emerged as a promising low-cost and scalable solution for autonomous driving. However, existing regression-based approaches often overlook inherent geometric priors, resulting in…
Over the past decade, lidars have become a cornerstone of robotics state estimation and perception thanks to their ability to provide accurate geometric information about their surroundings in the form of 3D scans. Unfortunately, most of…