Synthetic World Interface for Localization Algorithm Testing
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Solution Overview
Problem
Developing localization algorithms for autonomous systems and virtual reality applications is challenging due to the need for extensive testing across various sensor configurations, environmental conditions, and motion scenarios, which is costly and time-consuming.
Innovation Solution
A synthetic world interface is used to model digital environments, sensors, and motions, enabling the evaluation and development of localization algorithms through simulated scenarios. This approach includes a sensor platform simulator, motion orchestrator, environment orchestrator, experiment generator, and experiment runner to test hardware configurations and algorithms in a virtual environment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If extensive testing is conducted across various sensor configurations, environmental conditions, and motion scenarios, then localization algorithm reliability is improved, but development time and cost increase
Solution Approach 1:
The patent creates virtual copies of physical environments, sensors, and motion scenarios through synthetic data generation. Instead of conducting extensive physical testing, the system generates synthetic training data and test data that replicate real-world conditions, allowing comprehensive algorithm validation without the time and cost of physical prototypes and field testing
Solution Approach 2:
The system performs preliminary actions by generating synthetic training data before actual deployment. The synthetic data cloud service pre-generates diverse environmental conditions, sensor responses, and motion scenarios that would otherwise require extensive physical experimentation, enabling developers to train and validate algorithms in advance
2Reliability
If extensive testing is conducted across various sensor configurations, environmental conditions, and motion scenarios, then localization algorithm reliability is improved, but development cost increases
Solution Approach 1:
The patent replaces expensive physical testing infrastructure with virtual copies generated through synthetic data. The system creates digital representations of various sensor configurations, environmental conditions, and motion scenarios, eliminating the need for multiple physical prototypes, controlled environment chambers, and extensive field testing resources
Solution Approach 2:
The system uses computationally inexpensive synthetic data generation instead of expensive physical testing resources. The synthetic environments and sensor data can be rapidly generated and discarded, replacing the need for costly durable testing infrastructure that would need to withstand repeated physical experimentation
3Measurement precision
If multiple hardware configurations are tested to optimize localization, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent creates a universal synthetic testing platform that can evaluate multiple hardware configurations through software simulation rather than physical instantiation. The synthetic data cloud service generates sensor data compatible with various camera and IMU configurations, allowing a single testing system to evaluate diverse hardware setups without requiring each configuration to be physically built and tested
Solution Approach 2:
The system creates virtual copies of multiple hardware configurations through software models rather than physical prototypes. Each sensor configuration is represented by a digital twin that generates synthetic sensor responses, enabling comprehensive hardware evaluation without the complexity of managing multiple physical device variants
Data Source
AI summary
A synthetic world interface may be used to model digital environments, sensors, and motions for the evaluation, development, and improvement of localization algorithms. A synthetic data cloud service with a library of sensor primitives, motion generators, and environments with procedural and game-like capabilities, facilitates engineering design for a manufactural solution that has localization capabilities. In some embodiments, a sensor platform simulator operates with a motion orchestrator, an environment orchestrator, an experiment generator, and an experiment runner to test various candidate hardware configurations and localization algorithms in a virtual environment, advantageously speeding development and reducing cost. Thus, examples disclosed herein may relate to virtual reality (VR) or mixed reality (MR) implementations.