A Survey of the Multi-Sensor Fusion Object Detection Task in Autonomous Driving [PDF]
SensorsMulti-sensor fusion object detection is an advanced method that improves object recognition and tracking accuracy by integrating data from different types of sensors.
Hai Wang +3 more
doaj +4 more sources
A Review of Multi-Sensor Fusion SLAM Systems Based on 3D LIDAR
Remote Sensing, 2022 The ability of intelligent unmanned platforms to achieve autonomous navigation and positioning in a large-scale environment has become increasingly demanding, in which LIDAR-based Simultaneous Localization and Mapping (SLAM) is the mainstream of research
Xiaobin Xu +7 more
doaj +3 more sources
Multi-Sensor Fusion for Activity Recognition—A Survey [PDF]
Sensors, 2019 In Ambient Intelligence (AmI), the activity a user is engaged in is an essential part of the context, so its recognition is of paramount importance for applications in areas like sports, medicine, personal safety, and so forth. The concurrent use of multiple sensors for recognition of human activities in AmI is a good practice because the information ...
Antonio A Aguileta +2 more
exaly +5 more sources
AFTR: A Robustness Multi-Sensor Fusion Model for 3D Object Detection Based on Adaptive Fusion Transformer [PDF]
Sensors, 2023 Multi-modal sensors are the key to ensuring the robust and accurate operation of autonomous driving systems, where LiDAR and cameras are important on-board sensors.
Yan Zhang +6 more
doaj +2 more sources
Exploring the Unseen: A Survey of Multi-Sensor Fusion and the Role of Explainable AI (XAI) in Autonomous Vehicles [PDF]
SensorsAutonomous vehicles (AVs) rely heavily on multi-sensor fusion to perceive their environment and make critical, real-time decisions by integrating data from various sensors such as radar, cameras, Lidar, and GPS.
De Jong Yeong +2 more
doaj +2 more sources
A Review of Multi-Sensor Fusion in Autonomous Driving. [PDF]
Sensors (Basel)Multi-modal sensor fusion has become a cornerstone of robust autonomous driving systems, enabling perception models to integrate complementary cues from cameras, LiDARs, radars, and other modalities. This survey provides a structured overview of recent advances in deep learning-based fusion methods, categorizing them by architectural paradigms (e.g ...
Qian H, Wang M, Zhu M, Wang H.
europepmc +4 more sources
Multi-Sensor Fusion in Automated Driving: A Survey
IEEE Access, 2020 With the significant development of practicability in deep learning and the ultra-high-speed information transmission rate of 5G communication technology will overcome the barrier of data transmission on the Internet of Vehicles, automated driving is ...
Zhangjing Wang, Yu Wu, Qingqing Niu
doaj +3 more sources
A Survey on Multi-Sensor Fusion Perimeter Intrusion Detection in High-Speed Railways [PDF]
SensorsIn recent years, the safety issues of high-speed railways have remained severe. The intrusion of personnel or obstacles into the perimeter has often occurred in the past, causing derailment or parking, especially in the case of bad weather such as fog ...
Tianyun Shi +7 more
doaj +2 more sources
Review of the Method for Distributed Multi-sensor Multi-target Tracking
Leida xuebao, 2023 Multi-sensor multi-target tracking is a popular topic in the field of information fusion. It improves the accuracy and stability of target tracking by fusing multiple local sensor information.
Yajun ZENG +4 more
doaj +1 more source
An Outline of Multi-Sensor Fusion Methods for Mobile Agents Indoor Navigation
Sensors, 2021 Indoor autonomous navigation refers to the perception and exploration abilities of mobile agents in unknown indoor environments with the help of various sensors. It is the basic and one of the most important functions of mobile agents.
Yuanhao Qu +5 more
doaj +1 more source