Tesla, inc. (20240346816). DATA SYNTHESIS FOR AUTONOMOUS CONTROL SYSTEMS simplified abstract
Contents
- 1 DATA SYNTHESIS FOR AUTONOMOUS CONTROL SYSTEMS
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 DATA SYNTHESIS FOR AUTONOMOUS CONTROL SYSTEMS - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Key Features and Innovation
- 1.6 Potential Applications
- 1.7 Problems Solved
- 1.8 Benefits
- 1.9 Commercial Applications
- 1.10 Questions about the Technology
- 1.11 Original Abstract Submitted
DATA SYNTHESIS FOR AUTONOMOUS CONTROL SYSTEMS
Organization Name
Inventor(s)
Forrest Nelson Iandola of San Jose CA (US)
Donald Benton Macmillen of Hillsborough CA (US)
Anting Shen of Berkeley CA (US)
Harsimran Singh Sidhu of Fremont CA (US)
Paras Jagdish Jain of Cupertino CA (US)
DATA SYNTHESIS FOR AUTONOMOUS CONTROL SYSTEMS - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240346816 titled 'DATA SYNTHESIS FOR AUTONOMOUS CONTROL SYSTEMS
Simplified Explanation
An autonomous control system creates synthetic data to train computer models for detection and control algorithms by simulating sensor data from various perspectives.
Key Features and Innovation
- Generation of synthetic data representing sensor data from simulated environments.
- Training computer models for detection and control algorithms using the synthetic data.
- Simulating scenarios not included in existing training data.
- Removing unwanted effects or occlusions from sensor data of the environment.
Potential Applications
The technology can be applied in:
- Autonomous vehicles for training computer models.
- Surveillance systems for improving detection algorithms.
- Robotics for simulating different environments.
Problems Solved
The technology addresses:
- Limited training data for computer models.
- Inability to simulate specific scenarios.
- Challenges in removing unwanted effects from sensor data.
Benefits
- Improved performance of computer models.
- Enhanced simulation capabilities.
- Better detection and control algorithms.
Commercial Applications
- Autonomous vehicle industry for training AI models.
- Surveillance and security companies for improving detection systems.
- Robotics companies for simulating diverse environments.
Questions about the Technology
How does the technology improve the performance of computer models?
The technology enhances performance by generating synthetic data to train the models effectively.
What are the potential applications of this technology beyond autonomous vehicles?
The technology can also be applied in surveillance systems, robotics, and other fields requiring detection and control algorithms.
Original Abstract Submitted
an autonomous control system generates synthetic data that reflect simulated environments. specifically, the synthetic data is a representation of sensor data of the simulated environment from the perspective of one or more sensors. the system generates synthetic data by introducing one or more simulated modifications to sensor data captured by the sensors or by simulating the sensor data for a virtual environment. the autonomous control system uses the synthetic data to train computer models for various detection and control algorithms. in general, this allows autonomous control systems to augment training data to improve performance of computer models, simulate scenarios that are not included in existing training data, and/or train computer models that remove unwanted effects or occlusions from sensor data of the environment.
- Tesla, inc.
- Forrest Nelson Iandola of San Jose CA (US)
- Donald Benton Macmillen of Hillsborough CA (US)
- Anting Shen of Berkeley CA (US)
- Harsimran Singh Sidhu of Fremont CA (US)
- Paras Jagdish Jain of Cupertino CA (US)
- G06V10/82
- B60R11/04
- B60W40/02
- G05D1/81
- G06F18/214
- G06F18/241
- G06F30/15
- G06F30/20
- G06V10/764
- G06V20/58
- CPC G06V10/82