18577061. Method and Device for Generating Synthetic Training Data for an Ultrasonic Sensor Model simplified abstract (Robert Bosch GmbH)
Contents
Method and Device for Generating Synthetic Training Data for an Ultrasonic Sensor Model
Organization Name
Inventor(s)
Hakan Demirel of Pforzheim (DE)
Aditya Kumar Agarwal of Stuttgart (DE)
Method and Device for Generating Synthetic Training Data for an Ultrasonic Sensor Model - A simplified explanation of the abstract
This abstract first appeared for US patent application 18577061 titled 'Method and Device for Generating Synthetic Training Data for an Ultrasonic Sensor Model
The disclosure pertains to a method for creating synthetic training data for training a data-driven ultrasonic sensor model for a specific configuration of an ultrasonic sensor system with multiple sensor devices. The training data includes input data representing time-series data of received ultrasonic signals and output data indicating object characteristics of environmental objects within the sensor system's sensing range.
- The method involves generating synthetic training data for training a data-driven ultrasonic sensor model.
- The training data includes input data of time-series ultrasonic signals and output data of object characteristics within the sensor system's sensing range.
- The goal is to improve the accuracy and effectiveness of the ultrasonic sensor model through training with synthetic data.
- This innovation enables better performance of ultrasonic sensor systems in detecting and analyzing environmental objects.
- By using synthetic training data, the ultrasonic sensor model can be optimized for various configurations and scenarios.
Potential Applications: - Autonomous vehicles for object detection and collision avoidance - Industrial automation for object recognition and tracking - Robotics for navigation and obstacle avoidance
Problems Solved: - Enhances the accuracy and reliability of ultrasonic sensor systems - Improves object detection and characterization capabilities - Enables better performance in complex environments with multiple objects
Benefits: - Increased safety in autonomous systems - Enhanced efficiency in industrial processes - Improved navigation and obstacle avoidance for robots
Commercial Applications: Title: "Enhancing Ultrasonic Sensor Systems with Synthetic Training Data" This technology can be utilized in industries such as automotive, manufacturing, and robotics for improving the performance of ultrasonic sensor systems in various applications.
Prior Art: Readers can explore prior research on data-driven sensor models and synthetic training data generation techniques in the field of ultrasonic sensors to understand the existing knowledge and advancements in this area.
Frequently Updated Research: Researchers are continuously exploring new methods and algorithms for generating synthetic training data to enhance the capabilities of ultrasonic sensor systems. Stay updated on the latest developments in this field to leverage the most advanced techniques for sensor model training.
Questions about Ultrasonic Sensor Systems: 1. How does the use of synthetic training data impact the performance of ultrasonic sensor models? - Synthetic training data can improve the accuracy and effectiveness of ultrasonic sensor models by providing diverse scenarios for training. 2. What are the potential challenges associated with implementing synthetic training data in ultrasonic sensor systems? - Challenges may include ensuring the synthetic data accurately represents real-world scenarios and optimizing the training process for different sensor configurations.
Original Abstract Submitted
The disclosure relates to a computer-implemented method for generating synthetic training data for training of a data-driven ultrasonic sensor model for a given configuration of an ultrasonic sensor system having multiple ultrasonic sensor devices, wherein the training data includes input data representing time-series data of received ultrasonic signals and output data indicating object characteristics of environmental objects in a sensing range of the ultrasonic sensor system; comprising the steps of:
