Intel corporation (20240131704). AFFORDANCE-AWARE, MULTI-RESOLUTION, FREE-FORM OBJECT MANIPULATION PLANNING simplified abstract
Contents
- 1 AFFORDANCE-AWARE, MULTI-RESOLUTION, FREE-FORM OBJECT MANIPULATION PLANNING
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 AFFORDANCE-AWARE, MULTI-RESOLUTION, FREE-FORM OBJECT MANIPULATION PLANNING - 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 Unanswered Questions
- 1.11 Original Abstract Submitted
AFFORDANCE-AWARE, MULTI-RESOLUTION, FREE-FORM OBJECT MANIPULATION PLANNING
Organization Name
Inventor(s)
David Israel Gonzalez Aguirre of Hillsboro OR (US)
Javier Felip Leon of Hillsboro OR (US)
Javier Sebastian Turek of Beaverton OR (US)
Javier Perez-ramirez of North Plains OR (US)
Ignacio J. Alvarez of Portland OR (US)
AFFORDANCE-AWARE, MULTI-RESOLUTION, FREE-FORM OBJECT MANIPULATION PLANNING - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240131704 titled 'AFFORDANCE-AWARE, MULTI-RESOLUTION, FREE-FORM OBJECT MANIPULATION PLANNING
Simplified Explanation
The patent application describes a system for controlling end effectors by generating semantic labelled images to identify objects and their associated actions, allowing for the generation of plans to fulfill user commands.
- The system generates semantic labelled images based on image data to identify shapes of objects and their semantic labels.
- The system associates a set of actions with the identified objects.
- The system generates a plan by intersecting the set of actions associated with the objects and a second set of actions to satisfy user commands through end effector actuation.
Potential Applications
This technology could be applied in industrial automation, robotic assembly lines, and warehouse management systems.
Problems Solved
This technology solves the problem of efficiently controlling end effectors based on semantic information about objects in the environment.
Benefits
The benefits of this technology include improved efficiency in task execution, enhanced automation capabilities, and increased adaptability to changing environments.
Potential Commercial Applications
"Semantic Labelled Image-Based End Effector Control System for Industrial Automation"
Possible Prior Art
There may be prior art related to robotic control systems using semantic information for object manipulation, but further research is needed to identify specific examples.
Unanswered Questions
How does the system handle complex objects with multiple semantic labels?
The system's ability to handle complex objects with multiple semantic labels is not explicitly addressed in the abstract. Further details on this aspect would be beneficial for a comprehensive understanding of the technology.
What is the computational overhead of generating semantic labelled images and plans?
The abstract does not mention the computational resources required for generating semantic labelled images and plans. Understanding the computational overhead of this system is crucial for assessing its practicality and scalability.
Original Abstract Submitted
systems, apparatuses and methods may provide for controlling one or more end effectors by generating a semantic labelled image based on image data, wherein the semantic labelled image is to identify a shape of an object and a semantic label of the object, associating a first set of actions with the object, and generating a plan based on an intersection of the first set of actions and a second set of actions to satisfy a command from a user through actuation of one or more end effectors, wherein the second set of actions are to be associated with the command
