Objective-Effectuator Planner for Reliable Multi-Timeframe CGR Actions
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Solution Overview
Problem
Existing devices are ineffective in presenting representations of objects associated with actions in computer-generated reality (CGR) environments, particularly those involving characters or equipment, due to limitations in simulating and interacting with physical environments.
Innovation Solution
A planner is employed to generate a plan that satisfies the objective of an objective-effectuator by determining candidate plans, selecting one based on confidence scores, and triggering CGR representations to perform actions over multiple time frames, utilizing neural networks and engines to manage interactions and environmental conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If previously available devices present CGR environments, then virtual and augmented environments can be generated, but representations of objects associated with actions cannot be effectively presented
Solution Approach 1:
The system performs preliminary actions by generating a plan before executing actions in the CGR environment. The planner determines a sequence of actions that will satisfy the objective, ensuring that representations of objects associated with actions are presented effectively. This preliminary planning resolves the contradiction by establishing a reliable framework for presenting action-associated objects.
Solution Approach 2:
The system uses feedback mechanisms where the planner evaluates candidate plans and selects the best plan based on the objective. The effectuator then executes the selected plan, and the system monitors whether the objective is satisfied. This feedback loop ensures reliable presentation of CGR representations by continuously adjusting actions based on their effectiveness.
2Productivity
If a plan is generated to satisfy an objective across multiple time frames, then actions can be coordinated over time, but system complexity increases
Solution Approach 1:
The system segments the planning process into distinct components: generating candidate plans, selecting the best plan, and executing the selected plan. This segmentation manages complexity by breaking down the overall planning task into manageable sub-tasks, each handled by specific modules within the planner.
Solution Approach 2:
The planner is designed as a universal system that can handle multiple objectives and action types across different time frames. Rather than creating separate planning mechanisms for each scenario, the system uses a single multi-functional planner that adapts to various objectives, reducing overall system complexity.
3Measurement precision
If candidate plans are generated and selected based on selection criteria, then the best plan can be identified, but computational resources are consumed
Solution Approach 1:
The system generates a set of candidate plans rather than exhaustively exploring all possible plans. By generating a sufficient number of candidate plans to ensure the best plan is included, the system achieves accurate plan selection without consuming excessive computational resources. This partial action approach balances precision with energy efficiency.
Data Source
AI summary
In some implementations, a method includes obtaining an objective for a computer-generated reality (CGR) representation of an objective-effectuator. In some implementations, the objective is associated with a plurality of time frames. In some implementations, the method includes determining a plurality of candidate plans that satisfy the objective. In some implementations, the method includes selecting a first candidate plan of the plurality of candidate plans based on a selection criterion. In some implementations, the method includes effectuating the first candidate plan in order to satisfy the objective. In some implementations, the first candidate plan triggers the CGR representation of the objective-effectuator to perform a series of actions over the plurality of time frames associated with the objective.