▲Vehicle equipped with off-road autonomous driving technology from the Korea Institute of Machinery and Materials (Photo source: Captured video provided by the Korea Institute of Machinery and Materials)

Expected to be applied in various fields such as construction, industry, agricultural machinery, and defense unmanned vehicles
Stable off-road autonomous driving possible in unstructured environments such as bad weather

Off-road environmental recognition technology that can recognize foreign substances such as dust, mud, snow, and rain and remove them in real time when driving off-road in construction/agricultural machinery and defense unmanned vehicles (UGVs) has been developed for the first time in Korea.

It is expected that in the future, it will be widely used in extreme environments where it is difficult for people to operate, such as industrial machinery such as excavators, dump trucks, and search vehicles, as well as autonomous vehicles in the defense sector.

The research team led by Director Lee Han-min of the Industrial Machinery DX Laboratory of the Virtual Engineering Platform Research Center of the Korea Institute of Machinery and Materials (hereinafter referred to as KIMM) developed off-road environment recognition technologies such as ‘sensor protection module,’ ‘sensor signal compensation technology,’ and ‘driving area recognition and driving control technology’ applicable to off-road unmanned vehicles in mountainous terrain, watersides, and snowy roads, and transferred the related technologies to related companies.

Previously, there was no technology to protect sensors from foreign substances such as mud or muddy water in off-road environments.

LiDAR sensors can misrecognize dust, rain, snow, etc.There have also been cases where accidents occurred due to failure to detect obstacles.

In addition, there was no technology to recognize in real time not only protruding obstacles such as trees and rocks, but also terrain with varying heights such as cliffs and pits, making it difficult to apply autonomous driving technology to off-road environments.

The off-road environmental recognition technology developed this time has improved the speed and accuracy of key performance indicators such as sensor contamination recovery rate, sensor noise removal accuracy, and off-road driving area estimation accuracy by more than 1.5 times compared to existing technologies, thereby laying the foundation for stable use in off-road autonomous driving control.

The 'sensor protection and cleaning module' technology sprays a cleaning solution on muddy water or mud that may splash on the sensor surface during off-road autonomous driving and wipes it off with a wiper in real time, allowing it to be restored to the level before contamination occurred.

It also detects signals of small particles such as dust, snow, and rain that are likely to occur while driving. Off-road autonomous driving can be maintained more reliably even in unstructured environmental conditions such as bad weather through the 'sensor signal compensation' technology that removes the

'Drivable area estimation technology' and 'driving control technology' can find only the drivable area on bumpy roads such as obstacles, steep slopes, and potholes, automatically avoid obstacles, and control the vehicle's driving in real time, thereby avoiding accidents such as collisions with people or animals that suddenly appear during work.

Lee Han-min, head of the Industrial Machinery DX Lab at the Korea Institute of Machinery and Materials, said, "This is a key technology to solve environmental recognition problems that can frequently occur when unmanned vehicles are driving off-road," and added, "We will strive to apply it to industrial machinery such as excavators, dump trucks, and tractors to which autonomous driving will be applied in the future, as well as unmanned vehicles for defense such as tanks and search vehicles."

Meanwhile, the Korea Institute of Machinery and Materials reported that this research was conducted with support from the basic project of the Korea Institute of Machinery and Materials, ‘Development of Basic Technology for Autonomy of Industrial Mobile Work Machines.’