Deepen AI Introduces Radar and IMU Sensor Calibration: Loop-based Optimizer Improves Accuracy

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With new sensor pairings for radar and IMU-based sensors, the total number of calibration pairs supported now stands at ten.

Fremont, CA: "Our calibration suite is critical to help make the world safer & more productive in line with our mission. With the launch of the RADAR, IMU, and optimization loops, we have expanded our offerings to multiple new use cases for robotics, automotive, and drones" - Mohammad Musa, Co-Founder & CEO, Deepen AI.

Deepen AI launched radar and IMU sensor calibrations. Deepen Calibrate is a simple web browser-based calibration tool that supports intrinsic and extrinsic calibrations. Deepen Calibrate reduces the time required to calibrate multi-sensor data from hours to minutes, allowing for precise localization, mapping, sensor fusion perception, and control. Deepen Calibrate now enables a total of ten calibration pairings.

IMU calibration with Deepen Calibrate

1)  Radar to Camera (New)

2)  IMU to Vehicle (New)

3)  IMU Intrinsic (New)

4)  Vehicle to Camera

5)  LiDAR to Camera

6)  LiDAR to Vehicle

7)  Stereo Camera

8)  Non-overlapping Camera

9)  LiDAR to LiDAR

10) Camera intrinsic

Deepen AI is a Silicon Valley-based start-up that provides the first safety-first data lifecycle tools and services for autonomous systems. They have delighted clients of all sizes all over the world since their devices and services are customizable to meet the demands of companies and start-ups.

Deepen AI has also created a patented Loop-based Calibration Optimizer to detect and correct minor mistakes in many sensor calibrations, resulting in highly accurate sensor fusion. The calibration Optimiser can operate with many sensors in a closed loop. Deepen AI is able to eliminate mistakes and considerably boost sensor fusion accuracy by layering Calibration Optimiser on top of the standard procedures.

Deepen Calibrate simplifies and expedites the crucial work of sensor data calibration. Deepen Calibrate controls the complexity of the calibration process, assuring accuracy and making autonomous systems safer while also transforming a work that would normally demand the time of a Ph.D.-level engineer into something that anybody can perform.