Robotic Task Definition Using Delta Layers for Scene Consistency
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Solution Overview
Problem
Existing technologies face challenges in creating and managing complex scenes with numerous assets or objects, lacking standardization across different tools and platforms, leading to difficulties in data exchange, collaboration, and inconsistent task definitions for robotic systems.
Innovation Solution
Utilizing delta layers based on the Open Universal Scene Description (OpenUSD) format to efficiently represent scene changes, reducing memory consumption and computational load by storing only incremental updates, and enabling precise measurement of task adherence through comparison of delta layers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the entire scene is stored each time a change is made, then the scene data is complete and consistent, but memory consumption and computational resources increase significantly
Solution Approach 1:
The scene data is segmented into a base layer containing static scene information and delta layers containing only the changes. This segmentation allows the system to store only the differences (delta layers) rather than the entire scene data repeatedly, significantly reducing memory consumption while maintaining scene consistency through the base layer.
Solution Approach 2:
The invention extracts only the changed portions (delta information) from the complete scene data and stores them separately in delta layers. This extraction approach removes the redundancy of storing unchanged scene data multiple times, reducing memory requirements while preserving the ability to reconstruct complete scene states when needed.
2Adaptability or versatility
If proprietary formats are used by different software applications, then each application can optimize for its specific needs, but data exchange and collaboration between applications become difficult
Solution Approach 1:
The patent adopts the OpenUSD format as a universal scene representation standard that can be used across different software applications. This universal format allows various applications to read and write scene data using a common language, facilitating data exchange and collaboration while still allowing each application to optimize its specific functionality through the standardized interface.
3Quantity of substance
If delta layers are used to store only changes, then memory consumption and computational load are reduced, but the complexity of managing and comparing delta layers increases
Solution Approach 1:
The system incorporates feedback mechanisms where the robot executes tasks in the virtual scene, and the actual changes are fed back to generate delta layers. These delta layers are then compared with the intended task delta layers to measure task adherence. This feedback loop simplifies management by automatically generating and validating delta layers based on actual robot behavior rather than manual comparison.
Solution Approach 2:
The patent creates a virtual copy of the real-world robot performing tasks in a simulated environment. This virtual replica executes the same tasks in a controlled virtual scene, allowing the system to capture delta layers representing intended actions and compare them with actual executed actions. This copying approach simplifies delta layer management by providing a clear reference for what the robot should have done versus what it actually did.
Data Source
AI summary
Embodiments of the present disclosure relate to defining tasks in scenes using delta information. In operation, some embodiments first receive or generate scene data. Some embodiments then generate delta information indicating one or more changes within the scene data. For example, responsive to user input, particular embodiments generate the delta information, such as a delta layer. Generating such delta information is useful in various applications such as robotics, simulation, graphics rendering, gaming, autonomous driving, or the like. For instance, with respect to robotics, some embodiments store data corresponding to the delta information as at least part of a task definition for a robotic task. Some embodiments then responsively cause or train one or more real-world robotic components represented by one or more virtual robotic components to perform a task in a real-world scene represented by a virtual scene based on the delta information and the task definition.