Tesla, Inc. (20240378896). DETECTED OBJECT PATH PREDICTION FOR VISION-BASED SYSTEMS simplified abstract
Contents
DETECTED OBJECT PATH PREDICTION FOR VISION-BASED SYSTEMS
Organization Name
Inventor(s)
Nanda Kishore Vasudevan of Austin TX (US)
Dhiral Chheda of Austin TX (US)
DETECTED OBJECT PATH PREDICTION FOR VISION-BASED SYSTEMS - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240378896 titled 'DETECTED OBJECT PATH PREDICTION FOR VISION-BASED SYSTEMS
The abstract of the patent application describes a system that utilizes inputs from vision systems to generate simulations or predicted paths of travel for dynamic objects detected by the vision systems. This system can process the inputs to identify predicted paths of travel for dynamic objects and associate confidence values with these predictions.
- The system processes inputs from vision systems to generate simulations or predicted paths of travel for dynamic objects.
- It can identify multiple predicted paths of travel for each dynamic object detected.
- Confidence values are associated with the predicted paths to indicate the likelihood of each path occurring.
- The generated paths can be used as inputs for navigation systems, automated driving systems, and other related services.
- The system aims to improve the accuracy and reliability of predicting the paths of dynamic objects detected by vision systems.
Potential Applications: - Autonomous driving systems - Traffic management systems - Surveillance and security systems - Robotics and automation industries
Problems Solved: - Enhancing the accuracy of predicting the paths of dynamic objects - Improving the efficiency of navigation and automated driving systems - Increasing the reliability of vision system data analysis
Benefits: - Increased safety on the roads - Enhanced efficiency in transportation systems - Improved decision-making for autonomous vehicles - Enhanced security and surveillance capabilities
Commercial Applications: Title: Advanced Predictive Path Generation System for Autonomous Vehicles This technology can be utilized in the development of autonomous vehicles, traffic management systems, and surveillance solutions. It has the potential to revolutionize the way dynamic objects are tracked and predicted in various industries.
Questions about the technology: 1. How does this system improve the accuracy of predicting the paths of dynamic objects? 2. What are the potential implications of using confidence values to characterize predicted paths of travel?
Original Abstract Submitted
aspects of the present application correspond to utilization of a set of inputs from vision systems to generate simulations or predicted paths of travel for dynamic objects detected from the vision systems. illustratively, a service can process the set of inputs (e.g., the associated ground truth label data) collected from one or more vision systems (or additional services) to identify predicted paths of travel for any dynamic objects detected from the captured vision system information. typically, a plurality of predicted paths of travels can be generated such that more than one path of travel may be considered to meet or exceed a minimal threshold. the resulting predicted paths of travel can be further associated with confidence values that characterize the likelihood that any one predicted path of travel for a detected dynamic object will occur. the generated and processed paths can be provided or used as inputs for additional systems, such as navigation systems/services, semi-automated or automated driving systems/services and the like.
