An energy-efficient stream-based fpga implementation of feature extraction algorithm for lidar point clouds with effective local-search
Feature extraction is a fundamental and essential step in light detection and ranging
(LiDAR) based simultaneously localization and mapping (SLAM) algorithms. Considering …
(LiDAR) based simultaneously localization and mapping (SLAM) algorithms. Considering …
Stream-Based Ground Segmentation for Real-Time LiDAR Point Cloud Processing on FPGA
This paper presents a novel and fast approach for ground plane segmentation in a LiDAR
point cloud, specifically optimized for processing speed and hardware efficiency on FPGA …
point cloud, specifically optimized for processing speed and hardware efficiency on FPGA …
LiDAR Sensing Based Exponential Adaptive Cruise Control and Steering Assist for ADAS
Autonomous vehicles represent a groundbreaking advancement, prompting innovative
solutions for safer, more efficient transportation. These self-driving vehicles rely on …
solutions for safer, more efficient transportation. These self-driving vehicles rely on …
Low Latency Instance Segmentation by Continuous Clustering for LiDAR Sensors
A Reich, M Maehlisch - 2024 IEEE Intelligent Vehicles …, 2024 - ieeexplore.ieee.org
Low-latency instance segmentation of LiDAR point clouds is crucial in real-world
applications because it serves as an initial and frequently-used building block in a robot's …
applications because it serves as an initial and frequently-used building block in a robot's …
A range ambiguity classification algorithm for automotive LiDAR based on FPGA platform acceleration
H Li, S Xiang, L Zhang, J Zhu, S Wang, Y Wang - Frontiers in Physics, 2023 - frontiersin.org
In the past decade, the automotive light detection and ranging (LiDAR) has been
experiencing a rapid expansion stage. Many researchers have been involved in the …
experiencing a rapid expansion stage. Many researchers have been involved in the …
Low Latency Instance Segmentation by Continuous Clustering for Rotating LiDAR Sensors
A Reich, HJ Wuensche - arXiv preprint arXiv:2311.13976, 2023 - arxiv.org
Low-latency instance segmentation of LiDAR point clouds is crucial in real-world
applications because it serves as an initial and frequently-used building block in a robot's …
applications because it serves as an initial and frequently-used building block in a robot's …
Accelerating Point Cloud Ground Segmentation: From Mechanical to Solid-State Lidars
In this study, we propose a novel parallel processing method for point cloud ground
segmentation, aimed at the technology evolution from mechanical to solid-state Lidar (SSL) …
segmentation, aimed at the technology evolution from mechanical to solid-state Lidar (SSL) …
Implementation of Euclidean Clustering for Object Detection Using 3D LiDAR in an Autonomous Vehicle Prototype with Embedded System and ROS
PS Idrovo-Berrezueta, DA Dutan-Sanchez… - … Technology & Systems, 2024 - Springer
In the pursuit of advancing autonomous driving and automation across various domains,
precise obstacle detection stands as an essential feature. Leveraging LiDAR (Light …
precise obstacle detection stands as an essential feature. Leveraging LiDAR (Light …
A Novel Point Cloud Clustering Algorithm Integrating In-Vehicle Driver Monitoring
X Zhang, Z Li, H Liang, H Wang, H Xu… - 2023 IEEE …, 2023 - ieeexplore.ieee.org
Real-time, high-precision point cloud clustering algorithm is the prerequisite to achieve
accurate environment perception and scene understanding in human-machine co-driving …
accurate environment perception and scene understanding in human-machine co-driving …
Point Cloud Clustering System with DBSCAN Algorithm for Low-Resolution LiDAR
LiDAR point cloud clustering is a crucial part of object detection and recognition. However,
clustering enormous point cloud of LiDAR assigns a large processing load to an on-board …
clustering enormous point cloud of LiDAR assigns a large processing load to an on-board …