Related papers: A Low-Cost Portable Lidar-based Mobile Mapping Sys…
Currently, mobile robots are developing rapidly and are finding numerous applications in the industry. However, several problems remain related to their practical use, such as the need for expensive hardware and high power consumption…
Lidar is extensively used in the industry and mass-market. Due to its measurement accuracy and insensitivity to illumination compared to cameras, It is applied onto a broad range of applications, like geodetic engineering, self driving cars…
Environment mapping is an essential prerequisite for mobile robots to perform different tasks such as navigation and mission planning. With the availability of low-cost 2D LiDARs, there are increasing applications of such 2D LiDARs in…
Mobile smartphones compactly provide sensors such as cameras, IMUs, GNSS measurement units, and wireless and wired communication channels required for robotics projects. They are affordable, portable, and programmable, which makes them…
In the last decades, Light Detection And Ranging (LiDAR) technology has been extensively explored as a robust alternative for self-localization and mapping. These approaches typically state ego-motion estimation as a non-linear optimization…
Using different sensors in an autonomous vehicle (AV) can provide multiple constraints to optimize AV location estimation. In this paper, we present a low-cost GPS-assisted LiDAR state estimation system for AVs. Firstly, we utilize LiDAR to…
Lidar technology has evolved significantly over the last decade, with higher resolution, better accuracy, and lower cost devices available today. In addition, new scanning modalities and novel sensor technologies have emerged in recent…
Spherical robots offer unique advantages for mapping applications in hazardous or confined environments, thanks to their protective shells and omnidirectional mobility. This work presents two complementary spherical mapping systems: a…
Miniaturization of cameras and LiDAR sensors has enabled the development of wearable 3D mapping systems for emergency responders. These systems have the potential to revolutionize response capabilities by providing real-time, high-fidelity…
Reliable navigation in disaster-response and other unstructured indoor settings requires robots not only to avoid obstacles but also to recognise when those obstacles can be pushed aside. We present an adaptive, LiDAR and odometry-based…
Lidar odometry has attracted considerable attention as a robust localization method for autonomous robots operating in complex GNSS-denied environments. However, achieving reliable and efficient performance on heterogeneous platforms in…
This paper presents a real-time 3D mapping framework based on global matching cost minimization and LiDAR-IMU tight coupling. The proposed framework comprises a preprocessing module and three estimation modules: odometry estimation, local…
We propose a framework for tightly-coupled lidar inertial odometry via smoothing and mapping, LIO-SAM, that achieves highly accurate, real-time mobile robot trajectory estimation and map-building. LIO-SAM formulates lidar-inertial odometry…
LiDARs are being increasingly deployed for consumer imaging in handheld, wearable, and robotic applications. These sensors can capture the time-of-flight of light at picosecond resolution, which in principle, enables them to capture…
LiDAR odometry and mapping (LOAM) has been playing an important role in autonomous vehicles, due to its ability to simultaneously localize the robot's pose and build high-precision, high-resolution maps of the surrounding environment. This…
Integrating multiple LiDAR sensors can significantly enhance a robot's perception of the environment, enabling it to capture adequate measurements for simultaneous localization and mapping (SLAM). Indeed, solid-state LiDARs can bring in…
Long-term scene changes present challenges to localization systems using a pre-built map. This paper presents a LiDAR-based system that can provide robust localization against those challenges. Our method starts with activation of a mapping…
This article presents a comparative analysis of a mobile robot trajectories computed by various ROS-based SLAM systems. For this reason we developed a prototype of a mobile robot with common sensors: 2D lidar, a monocular and ZED stereo…
Autonomous robotic systems heavily rely on environment knowledge to safely navigate. For search & rescue, a flying robot requires robust real-time perception, enabled by complementary sensors. IMU data constrains acceleration and rotation,…
We present an efficient multi-sensor odometry system for mobile platforms that jointly optimizes visual, lidar, and inertial information within a single integrated factor graph. This runs in real-time at full framerate using fixed lag…