Robotics Event Logging for Mission Replay and Debugging
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Solution Overview
Problem
Existing robotics control applications face challenges in debugging and improving due to the impracticality of storing large sensor data and precisely measuring timing information, which hinders accurate reproduction of mission failures.
Innovation Solution
A system that logs event information from robotic missions, including timestamps and actor updates, allows for the replay of decisions made by the robotics control application through simulations, and trains machine learning models to detect errors and generate control decisions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If original sensor data is stored for extended periods to reproduce mission failures, then debugging capability is improved, but storage requirements become impractical due to large data size
Solution Approach 1:
The patent extracts only the essential event information (decisions, actions, timestamps) from the vast sensor data, discarding the bulk of the raw sensor data while retaining the critical information needed for debugging. This allows reproduction of mission failures without storing the entire sensor data streams.
Solution Approach 2:
The patent creates a simplified copy of the mission events in the form of event logs that capture decisions and actions taken by the robotics control application. This copy is sufficient for reproduction and debugging purposes without requiring the original large sensor data files.
2Measurement precision
If precise timing information is measured to reproduce failures accurately, then debugging precision is improved, but measurement complexity and difficulty increase
Solution Approach 1:
The patent changes the timing parameter from high-precision absolute timestamps to relative event sequencing. Instead of requiring precise measurement of absolute timing across all sensor data, the system tracks the sequence of events and uses simplified timestamps that are sufficient for reproducing the logical flow of decisions and actions.
3Loss of information
If large sensor data is stored and processed, then completeness of mission analysis is improved, but processing time and computational resources increase
Solution Approach 1:
The patent extracts only the decision-making events and actions from the sensor data, filtering out redundant sensor information. This selective extraction maintains the completeness of the analysis for debugging purposes while dramatically reducing the amount of data that needs to be processed and stored.
Data Source
AI summary
Systems and techniques to improve a robotics control application are described herein. In at least one embodiment, event information is generated by one or more robots performing a mission. The event information indicates one or more determinations made by the one or more robots. The event information is stored in a log, and the stored event information can be used to simulate the generating of decisions to control the one or more robots.