Nvidia corporation (20240161341). SENSOR CALIBRATION FOR AUTONOMOUS SYSTEMS AND APPLICATIONS simplified abstract
Contents
- 1 SENSOR CALIBRATION FOR AUTONOMOUS SYSTEMS AND APPLICATIONS
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 SENSOR CALIBRATION FOR AUTONOMOUS SYSTEMS AND APPLICATIONS - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Potential Applications
- 1.6 Problems Solved
- 1.7 Benefits
- 1.8 Potential Commercial Applications
- 1.9 Possible Prior Art
- 1.10 Original Abstract Submitted
SENSOR CALIBRATION FOR AUTONOMOUS SYSTEMS AND APPLICATIONS
Organization Name
Inventor(s)
Ayon Sen of Santa Clara 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 20240161341 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 and/or another image sensor using image feature correspondences and the assumption that image features are locally planar.
- The method involves constructing an optimization problem to minimize a geometric loss function that encodes the notion that corresponding image features are views of the same point on a locally planar surface constructed from lidar data.
- By using this method, structure estimation is removed from the optimization problem, simplifying the calibration process.
Potential Applications
This technology can be applied in autonomous or semi-autonomous systems that require accurate sensor calibration, such as self-driving cars, drones, or robotic systems.
Problems Solved
- Accurate calibration of image sensors with lidar sensors and other image sensors. - Simplification of the calibration process by removing structure estimation from the optimization problem.
Benefits
- Improved accuracy in sensor calibration. - Enhanced performance of autonomous or semi-autonomous systems. - Reduction in calibration complexity and time.
Potential Commercial Applications
"Sensor Calibration Method for Autonomous Systems" can be used in industries such as automotive, robotics, and aerospace for improving the performance and reliability of autonomous systems.
Possible Prior Art
One possible prior art could be the use of traditional calibration methods that involve complex structure estimation processes, leading to longer calibration times and potentially less accurate results.
Unanswered Questions
How does this method compare to traditional sensor calibration techniques?
This article does not provide a direct comparison between the proposed method and traditional sensor calibration techniques in terms of accuracy, efficiency, or complexity.
What are the potential limitations or challenges of implementing this calibration method in real-world applications?
The article does not address any potential limitations or challenges that may arise when implementing this calibration method in practical autonomous systems or 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.
