TY - CHAP
T1 - Collision Avoidance Systems and Emerging Bio-inspired Sensors for Autonomous Vehicles
AU - Jayachandran, Darsith
AU - Das, Saptarshi
N1 - Publisher Copyright:
© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2022.
PY - 2022/1/1
Y1 - 2022/1/1
N2 - Collision detection and avoidance are critical tasks for manned and unmanned vehicles, flying drones, and robots navigating complex terrestrial and extraterrestrial geographies. In this book chapter, we review different state-of-the-art collision avoidance sensors such as Radar, LiDAR, ultrasonics, and imaging systems. We also discuss emerging bio-inspired alternatives for low-power design of collision avoidance systems. Finally, we conclude with the prospect of sensor fusion technology for collision avoidance.
AB - Collision detection and avoidance are critical tasks for manned and unmanned vehicles, flying drones, and robots navigating complex terrestrial and extraterrestrial geographies. In this book chapter, we review different state-of-the-art collision avoidance sensors such as Radar, LiDAR, ultrasonics, and imaging systems. We also discuss emerging bio-inspired alternatives for low-power design of collision avoidance systems. Finally, we conclude with the prospect of sensor fusion technology for collision avoidance.
UR - http://www.scopus.com/inward/record.url?scp=85166076787&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85166076787&partnerID=8YFLogxK
U2 - 10.1007/978-3-031-11506-6_6
DO - 10.1007/978-3-031-11506-6_6
M3 - Chapter
AN - SCOPUS:85166076787
SN - 9783031115059
SP - 121
EP - 142
BT - Near-sensor and In-sensor Computing
PB - Springer International Publishing
ER -