Abstract
Obstacle detection is one of the most important parts of vehicle driving in Unmanned Autonomous Vehicles (UAV), which has been the subject of extensive research with the advancement of sensor fusion technology. Obstacle detection is a challenging process that considers the variety of obstacles, sensor properties, and ambient factors. Although research into driver assistance or autonomous driving systems for any environments has been thorough. Due to the sensing constraints in range, signal characteristics, and operating circumstances of detection, a single type of sensor finds it challenging to satisfy the objectives of obstacle detection. This drives researchers and engineers to develop multi-sensor fusion and system integration methodologies. This survey intends to provide users with a framework for selecting sensors based on their performance needs and application scenarios by outlining the key factors for onboard multi-sensor configuration of autonomous vehicles in the any environment conditions. Modern multi-sensor fusion techniques are discussed, along with system prototypes, and the relevant heterogeneous sensor configurations are linked. Finally, difficulties and new technologies are discussed for further research.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
