Curium drives several technologies capable of performing rapid and automatic calibration of sensors in fully automated systems such as autonomous vehicles.

Currently, Curium is deploying increasingly advanced technologies into vehicles that are creeping up the level of autonomy from Level 2 to Level 4. This project aims to enhance these current systems and elevate these manufacturers to deploy Level 5 autonomous vehicles.

The current problem is that sensors can become miscalibrated for any number of environmental reasons. With these sensors providing erroneous reading, the decision-making algorithms will make incorrect decisions leading to injury or death to vehicle owners, occupants, or pedestrians.

By monitoring and automatically calibrating the sensors in real-time, we can improve uptime and reduce the likelihood of miscalibrations leading to a dangerous situation.

The apprentice will work with the Curium Development Team to develop novel techniques to measure, monitor, and adjust sensor data in near real-time for Automotive use-cases. The challenges are to problem-solve the issues related to modelling 3D environments in a highly efficient manner to leverage the limited computational resources that are typically embedded into onboard vehicle systems. 3D environments will be modelled primarily using Inertial Measurement Units (IMUs), LIDAR, RADAR, and Camera sensors and deployed on computational platforms such as (but not limited to) the NVIDIA platform.