UAV Event Tracking Through Correlated Process Logs and Movement Records
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Solution Overview
Problem
Current systems lack effective methods for precisely tracking and analyzing input signals leading to specific events in movable objects, such as crashes or collisions, making it difficult to distinguish between user programming errors and API or back-end errors.
Innovation Solution
A method involving the creation of a process log for a movable object manager and a movement record, which are correlated to analyze movable object events, enabling real-time or post-operation analysis of performance and events.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional tracking methods are used, then system simplicity is maintained, but measurement precision of error sources deteriorates
Solution Approach 1:
The tracking system is segmented into two independent but correlated components: process logs (software environment) and movement records (physical environment). This segmentation allows precise error source identification by comparing timestamps and events across both segments, resolving the contradiction between measurement precision and system complexity.
Solution Approach 2:
Timestamps serve as an intermediary element that bridges the process log and movement record. By correlating events through shared timestamps, the system achieves precise error tracking without requiring direct complex integration between software and hardware components.
2Reliability
If detailed performance tracking is implemented, then reliability of error analysis is improved, but loss of time for data processing increases
Solution Approach 1:
Both process logs and movement records are continuously collected and timestamped during normal operation, preparing the data in advance. When an error occurs, the pre-collected data can be immediately correlated without delay, improving reliability while minimizing analysis time.
Solution Approach 2:
Manual error analysis is replaced by automated correlation of timestamped logs and records. The system automatically matches events between software and physical domains, reducing both the time required for analysis and the potential for human error in interpretation.
Data Source
AI summary
A system for tracking and analyzing performance of a movable object and methods of making and using the same. Movable object performance can be tracked by creating a process log for a movable object manager of the movable object, and creating a movement record of the movable object for comparison to the process log. The process log can include, for example, records of application call processes to a movable object interface, protocol call processes transmitted to and from the movable object, and/or metadata. A movable object event can be analyzed by correlating the process log with the movement record. The present systems and methods are particularly suitable for tracking and analysis of unmanned aerial vehicles (UAV).