Cutting-edge off-road technology for detecting and removing substances such as dust, mud, snow, and rain during autonomous off-road vehicle operation is now a game-changer in the field of industrial machinery and military vehicle innovation.
The Korea Institute of Machinery and Materials (KIMM) has successfully pioneered the development of off-road environment recognition technologies for driving in rugged, challenging terrains, such as mountains, riverbanks, and snowy regions. These groundbreaking technologies encompass sensor protection and cleaning, sensor signal correction, and drivable area recognition features, which are expected to revolutionize the off-road autonomous driving sector.
One of the novel advancements in this field is the “sensor protection and cleaning module” technologies, which involve the utilization of detergents to eliminate muddy water or dirt splashes on sensors during off-road self-driving. In addition, sensor signal correction technology has been developed to remove small-sized extraneous particles like dust, snow, and rain, ensuring stable driving conditions even in adverse weather conditions.
Furthermore, the “drivable area estimation technology” has proven to be a remarkable breakthrough, enabling the detection and avoidance of obstacles such as steep slopes, potholes, and rough roads, thereby preventing collisions with objects. The KIMM has also introduced the “driving control technology” to enable real-time vehicle control by selecting the necessary functions as per the driving conditions.
Prior to these developments, there were no technologies suitable for off-road environments, where dirt and mud tend to adhere to vehicles. Additionally, the challenge of removing sensor signals of extraneous substances such as dust, snow, or rain in real-time from LiDAR or camera sensor signals, and the issue of accurately estimating drivable areas have also been effectively addressed by these advancements.
The new off-road environment recognition technologies have enhanced processing speed by over 1.5 times, while maintaining superior performance indicators such as sensor contamination recovery rate and off-road drivable area estimation accuracy. Senior Researcher Han-Min Lee of the KIMM emphasized the significance of these technologies in addressing the dangerous obstacles encountered during off-road autonomous driving, expressing a strong commitment to their potential application in the self-driving of industrial machinery and military vehicles.
In conclusion, the pioneering work of the KIMM in this domain has set a new benchmark for the industry, and their efforts are poised to make a substantial impact on the future of off-road self-driving vehicles.
Citation: Environment recognition technologies for off-road self-driving with improved real-time processing performance (2024, April 17) retrieved 17 April 2024 from https://techxplore.com/news/2024-04-environment-recognition-technologies-road-real.html