SLAM Sensor Synchronization Using Motion-Data Time Alignment
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Solution Overview
Problem
Existing methods for localizing sensor data in 3D-map-data generated by SLAM systems face challenges such as increased computational complexity and the need for direct hardware interaction or compatibility between sensor systems and 3D-camera systems, limiting the range of compatible devices.
Innovation Solution
A software-based synchronization method that correlates motion-data from different devices to establish a common time reference, allowing integration of sensor data with 3D-map-data without requiring hardware synchronization, using a data processing unit to align timing-information and motion-data from separate 3D-camera and sensor-devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If direct hardware interaction or compatibility is required between sensor system and 3D-camera system for localization, then measurement precision is improved, but device complexity and ease of operation deteriorate
Solution Approach 1:
The patent introduces motion data as an intermediary element that bridges the sensor system and 3D-camera system. Instead of requiring direct hardware interaction, the system uses motion data captured by both devices to establish timing relationships and correlate sensor data with 3D-map data, thereby achieving localization without complex hardware integration
Solution Approach 2:
The patent replaces the mechanical/hardware synchronization system with a software-based correlation system. By substituting direct hardware interaction with algorithmic processing of motion data and timing information, the system achieves the same localization function with reduced hardware complexity and improved ease of operation
2Reliability
If direct hardware interaction is required between sensor system and 3D-camera system, then reliability of data association is improved, but adaptability deteriorates
Solution Approach 1:
The patent creates a universal data association method that works across different sensor systems and 3D-camera systems without requiring hardware-specific integration. By using motion data and timing information as a common interface, the system can associate data from diverse device combinations, thereby improving adaptability while maintaining reliability through consistent correlation algorithms
3Ease of operation
If computational methods are used for localizing sensor data in 3D-map-data, then ease of operation is improved, but computational complexity increases
Solution Approach 1:
The patent extracts the essential synchronization information (motion data and timing information) from the complex data streams and uses only these extracted elements for correlation. This selective extraction approach simplifies the computational process while maintaining the ability to accurately localize sensor data in 3D-map-data, thereby reducing computational complexity while preserving ease of operation
Data Source
AI summary
The disclosure relates to a simultaneous localisation and mapping, SLAM, device a data processing unit, computer program and associated method for receiving first-sensor-data, first-motion-data and first-timing-information associated with the first-sensor-data and the first-motion-data; receiving second-sensor-data, second-motion-data and second-timing-information associated with the second-sensor-data and the second-sensor-motion-data; and correlating the first-motion-data with the second-motion-data to identify a relationship between the first-timing-information and the second-timing-information, in which the identified relationship between the first-timing-information and the second-timing-information defines one or more associations between the first-sensor-data and the second-sensor-data.