LAB22 - EnviroSense

In an era in which safety, efficiency, and sustainability of mobility pose central challenges, driver assistance systems - despite significant progress - often encounter their limits. Especially in unexpected or complex situations, systems may react inadequately. The key to overcoming these challenges lies in the integration of advanced detection and prediction systems, supported by sophisticated sensors and Artificial Intelligence (AI).

Aim

The project's aim is to develop a robot equipped with advanced sensors for reliable environmental detection and prediction. A special focus is on LiDAR sensors, which emit invisible light beams. By measuring the time until reflections of the beam return to the sensor, distances can be calculated. Novel solid state LiDAR do not require moving parts and come with additional advantages. Other sensors such as color cameras and acceleration sensors are used in conjunction with them and can be combined. The data collected by the robot can be used by researchers in ICM and beyond to develop innovative AI approaches for future mobility.

Approach

• Equipping a robot with state-of-the-art sensors
• Collecting sensor data in traffic situations

Benefit

The data thus obtained will be used to develop novel AI methods that offer unprecedented reliability in environmental detection. These will also assess the uncertainty of the information gathered about the environment. The robot and the data it collects will be made available to partners, serving as a benchmark for comparing new approaches with existing methods.