18166121. SENSOR CALIBRATION FOR AUTONOMOUS SYSTEMS AND APPLICATIONS simplified abstract (NVIDIA Corporation)

SENSOR CALIBRATION FOR AUTONOMOUS SYSTEMS AND APPLICATIONS

Organization Name

NVIDIA Corporation

Inventor(s)

Ayon Sen of Santa Clara CA (US)

Gang Pan of Fremont CA (US)

Cheng-Chieh Yang of Seattle WA (US)

Yue Wu of Mountain View CA (US)

SENSOR CALIBRATION FOR AUTONOMOUS SYSTEMS AND APPLICATIONS - A simplified explanation of the abstract

This abstract first appeared for US patent application 18166121 titled 'SENSOR CALIBRATION FOR AUTONOMOUS SYSTEMS AND APPLICATIONS

Simplified Explanation

The patent application describes a method for calibrating an image sensor with a LiDAR sensor using image feature correspondences and the assumption that image features are locally planar. This method involves constructing an optimization problem to minimize a geometric loss function that encodes the idea that corresponding image features are views of the same point on a locally planar surface generated from LiDAR data.

• Explanation of the patent:
• Method for calibrating an image sensor with a LiDAR sensor using image feature correspondences and assuming locally planar image features.
• Constructing an optimization problem to minimize a geometric loss function that encodes the relationship between corresponding image features and a locally planar surface generated from LiDAR data.

1. 1. 1. Potential Applications:

- Autonomous vehicles - Robotics - Augmented reality systems

1. 1. 1. Problems Solved:

- Accurate calibration of image sensors with LiDAR sensors - Improved accuracy in determining parameters for sensor configuration

1. 1. 1. Benefits:

- Enhanced performance of autonomous or semi-autonomous systems - Increased reliability in sensor data fusion - Improved accuracy in object detection and tracking

1. 1. 1. Potential Commercial Applications:
         1. Optimizing Sensor Calibration for Autonomous Systems

- Optimizing sensor calibration for autonomous vehicles - Enhancing sensor fusion in robotics applications

1. 1. 1. Possible Prior Art:

- Existing methods for sensor calibration using traditional calibration techniques - Prior art related to LiDAR sensor calibration techniques

1. 1. 1. 1. Unanswered Questions:
         2. How does this method compare to traditional sensor calibration techniques?

This article does not provide a direct comparison between this method and traditional sensor calibration techniques. Further research or testing may be needed to evaluate the effectiveness of this approach compared to existing methods.

1. 1. 1. 1. What are the limitations of using image feature correspondences for sensor calibration?

The article does not discuss any potential limitations or challenges associated with using image feature correspondences for sensor calibration. It would be important to investigate any potential drawbacks or constraints of this approach in real-world applications.

Original Abstract Submitted

In various examples, sensor configuration for autonomous or semi-autonomous systems and applications is described. Systems and methods are disclosed that may use image feature correspondences between camera images along with an assumption that image features are locally planar to determine parameters for calibrating an image sensor with a LiDAR sensor and/or another image sensor. In some examples, an optimization problem is constructed that attempts to minimize a geometric loss function, where the geometric loss function encodes the notion that corresponding image features are views of a same point on a locally planar surface (e.g., a surfel or mesh) that is constructed from LiDAR data generated using a LiDAR sensor. In some examples, performing such processes to determine the calibration parameters may remove structure estimation from the optimization problem.