View source for 20240085914.DETERMINING PERCEPTION ZONES FOR OBJECT DETECTION IN AUTONOMOUS SYSTEMS AND APPLICATIONS simplified abstract (nvidia corporation)

=DETERMINING PERCEPTION ZONES FOR OBJECT DETECTION IN AUTONOMOUS SYSTEMS AND APPLICATIONS=


==Organization Name==

[[:Category:nvidia corporation|nvidia corporation]]


[[Category:nvidia corporation]]

==Inventor(s)==

[[:Category:Sever Ioan Topan of Burnaby (CA)|Sever Ioan Topan of Burnaby (CA)]][[Category:Sever Ioan Topan of Burnaby (CA)]]

[[:Category:Karen Yan Ming Leung of Los Altos CA (US)|Karen Yan Ming Leung of Los Altos CA (US)]][[Category:Karen Yan Ming Leung of Los Altos CA (US)]]

[[:Category:Yuxiao Chen of Sunnyvale CA (US)|Yuxiao Chen of Sunnyvale CA (US)]][[Category:Yuxiao Chen of Sunnyvale CA (US)]]

[[:Category:Pritish Tupekar of Santa Clara CA (US)|Pritish Tupekar of Santa Clara CA (US)]][[Category:Pritish Tupekar of Santa Clara CA (US)]]

[[:Category:Edward Fu Schmerling of Los Altos CA (US)|Edward Fu Schmerling of Los Altos CA (US)]][[Category:Edward Fu Schmerling of Los Altos CA (US)]]

[[:Category:Hans Jonas Nilsson of Los Gatos CA (US)|Hans Jonas Nilsson of Los Gatos CA (US)]][[Category:Hans Jonas Nilsson of Los Gatos CA (US)]]

[[:Category:Michael Cox of Menlo Park CA (US)|Michael Cox of Menlo Park CA (US)]][[Category:Michael Cox of Menlo Park CA (US)]]

[[:Category:Marco Pavone of Stanford CA (US)|Marco Pavone of Stanford CA (US)]][[Category:Marco Pavone of Stanford CA (US)]]

==DETERMINING PERCEPTION ZONES FOR OBJECT DETECTION IN AUTONOMOUS SYSTEMS AND APPLICATIONS - A simplified explanation of the abstract==


This abstract first appeared for US patent application 20240085914 titled 'DETERMINING PERCEPTION ZONES FOR OBJECT DETECTION IN AUTONOMOUS SYSTEMS AND APPLICATIONS

==Simplified Explanation==

The patent application describes techniques for determining perception zones for object detection using dynamic models associated with an ego-machine and an object, as well as possible interactions between them. The system then uses the perception zone to validate a perception system or determine safety-critical objects.

* Dynamic models associated with an ego-machine and an object are used to determine perception zones.
* The system can validate a perception system by checking if an object is within the perception zone.
* Safety-critical objects can be identified based on their location within the perception zone.

== Potential Applications ==
The technology can be applied in autonomous vehicles, robotics, surveillance systems, and industrial automation for improved object detection and safety.

== Problems Solved ==
- Enhanced object detection accuracy
- Identification of safety-critical objects
- Validation of perception systems

== Benefits ==
- Increased safety in various applications
- Improved efficiency in object detection
- Enhanced decision-making capabilities

== Potential Commercial Applications ==
"Enhancing Object Detection and Safety in Autonomous Vehicles and Robotics"

== Possible Prior Art ==
Prior art may include existing object detection systems in autonomous vehicles and robotics that use dynamic models for perception zones.

== Unanswered Questions ==

=== How does the system handle dynamic environments where objects are constantly moving? ===
The system may need to continuously update the perception zones based on real-time data to account for moving objects.

=== What are the limitations of the perception zones in terms of object size and shape? ===
The system may have constraints in accurately detecting very small or irregularly shaped objects within the perception zone.


==Original Abstract Submitted==

in various examples, techniques for determining perception zones for object detection are described. for instance, a system may use a dynamic model associated with an ego-machine, a dynamic model associated with an object, and one or more possible interactions between the ego-machine and the object to determine a perception zone. the system may then perform one or more processes using the perception zone. for instance, if the system is validating a perception system of the ego-machine, the system may determine whether a detection error associated with the object is a safety-critical error based on whether the object is located within the perception zone. additionally, if the system is executing within the ego-machine, the system may determine whether the object is a safety-critical object based on whether the object is located within the perception zone.



[[Category:G05D1/02]]
[[Category:G06V20/58]]