Navigating an Automated Driving Vehicle via the Early Fusion of Multi-Modality

Haris, Malik; Głowacz, Adam

doi:10.3390/s22041425

Cited by 16 publications

(11 citation statements)

References 72 publications

(86 reference statements)

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“…Multimodal sensors for object detection in marine environments use color-based learning and can only be used during the daytime [14]. Sensor fusion for autonomous vehicle navigation is a method that uses only the active depth information from the RGB and LiDAR cameras [15,16]. The method using video and sound can only respond to intruders in a room [17].…”

Section: Introductionmentioning

confidence: 99%

Design of Multimodal Sensor Module for Outdoor Robot Surveillance System

et al. 2022

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Recent studies on surveillance systems have employed various sensors to recognize and understand outdoor environments. In a complex outdoor environment, useful sensor data obtained under all weather conditions, during the night and day, can be utilized for application to robots in a real environment. Autonomous surveillance systems require a sensor system that can acquire various types of sensor data and can be easily mounted on fixed and mobile agents. In this study, we propose a method for modularizing multiple vision and sound sensors into one system, extracting data synchronized with 3D LiDAR sensors, and matching them to obtain data from various outdoor environments. The proposed multimodal sensor module can acquire six types of images: RGB, thermal, night vision, depth, fast RGB, and IR. Using the proposed module with a 3D LiDAR sensor, multimodal sensor data were obtained from fixed and mobile agents and tested for more than four years. To further prove its usefulness, this module was used as a monitoring system for six months to monitor anomalies occurring at a given site. In the future, we expect that the data obtained from multimodal sensor systems can be used for various applications in outdoor environments.

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Section: Introductionmentioning

confidence: 99%

Design of Multimodal Sensor Module for Outdoor Robot Surveillance System

et al. 2022

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“…The 2D image information transmitted by the camera is combined with the information provided by the laser. Depth information enables the vehicle to perceive 3D objects, such as people, cars, and the infrastructure around them, as well as transmit the 3D object information to the control unit to enable the vehicle to accurately avoid these obstacles [ 9 , 10 , 11 , 12 ]. Currently, many tech companies are investing in autonomous driving, such as Baidu, Huawei, Tesla, and Google.…”

Section: Introductionmentioning

confidence: 99%

A Review of Vision-Laser-Based Civil Infrastructure Inspection and Monitoring

Zhou

Tang

et al. 2022

Sensors

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Structural health and construction security are important problems in civil engineering. Regular infrastructure inspection and monitoring methods are mostly performed manually. Early automatic structural health monitoring techniques were mostly based on contact sensors, which usually are difficult to maintain in complex infrastructure environments. Therefore, non-contact infrastructure inspection and monitoring techniques received increasing interest in recent years, and they are widely used in all aspects of infrastructure life, owing to their convenience and non-destructive properties. This paper provides an overview of vision-based inspection and vision–laser-based monitoring techniques and applications. The inspection part includes image-processing algorithms, object detection, and semantic segmentation. In particular, infrastructure monitoring involves not only visual technologies but also different fusion methods of vision and lasers. Furthermore, the most important challenges for future automatic non-contact inspections and monitoring are discussed and the paper correspondingly concludes with state-of-the-art algorithms and applications to resolve these challenges.

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“…Automotive sensors are broadly applied to give real-time data to the AVs [8]. The Exteroceptive sensors which perceive the environment like radars, cameras, and lidars are the most important part of the measurement system [9,10]. Although cameras serve excellent visual results for objects around an AV, the weather conditions can significantly influence the reliability and robustness of detections.…”

Section: Introductionmentioning

confidence: 99%

A Novel Triple Radar Arrangement for Level 2 ADAS Detection System in Autonomous Vehicles

Enayati¹,

Asef²,

Jonnalagadda³

2022

Preprint

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The main functions of the automated systems rely on the advanced sensors for detection and perception of the environment around the vehicle. Radars and cameras are commonly utilized to detect the potential obstacles and vehicles ahead on the road. Nevertheless, cameras can generate spurious detections in the extreme weather conditions such as fog, rain, dust, snow, dark, and heavy sunlight in the sky. Due to limitations in vertical field view of the radars, single radars are not reliable to detect the height of the targets precisely. In this paper, a triple radar arrangement (long-range, medium-range, and short-range radars) based on sensor fusion technique is proposed to detect objects with different size in level 2 Advanced Driver-Assistance (ADAS) system. The typical objects including truck, pedestrians, and animals are detected in different scenarios. The developed model considered ISO 26262 and ISO/PAS 21448 to reasonably address insufficient robustness and inability of the sensors. The models of sensor and level 2 ADAS systems are developed using MATLAB toolbox and Simulink. Sensor detection performance is determined by running simulations with triple radar setup. Obtained results demonstrate that the proposed approach generates accurate detections of targets in all tested scenarios.

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Navigating an Automated Driving Vehicle via the Early Fusion of Multi-Modality

Cited by 16 publications

References 72 publications

Design of Multimodal Sensor Module for Outdoor Robot Surveillance System

Design of Multimodal Sensor Module for Outdoor Robot Surveillance System

A Review of Vision-Laser-Based Civil Infrastructure Inspection and Monitoring

A Novel Triple Radar Arrangement for Level 2 ADAS Detection System in Autonomous Vehicles

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