Stop Trajectory Control for Mobile Machine Failure Handling
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Solution Overview
Problem
Existing mobile machine automation systems face challenges in accurately detecting failures, leading to potential delays or mission failures due to conservative or aggressive fault detection mechanisms, which can result in unexpected behavior or incomplete tasks.
Innovation Solution
An automation system that generates and manages stop trajectories based on sensor data to safely bring a mobile machine to a stop in case of system failures, using a combination of high-performance and environmentally-hardened computers to process sensor data and control actuators, with features like exception stop trajectories to handle late-revealed obstacles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the automation controller is too conservative and detects failure more often than failure actually occurs, then safety is improved, but productivity deteriorates due to unexpected behavior and payload delays
Solution Approach 1:
The system pre-computes multiple stop trajectories at different locations along the pathway before failure occurs. When failure is detected, the controller can immediately switch to an appropriate pre-computed trajectory without delay, maintaining both safety and productivity by eliminating the computational lag that would otherwise cause payload delays.
Solution Approach 2:
The failure detection mechanism dynamically adjusts its sensitivity and response based on the current operating context. The controller evaluates multiple factors (sensor data quality, trajectory completion progress, environmental conditions) to determine whether a detected anomaly represents actual failure or temporary disturbance, reducing false positives while maintaining safety.
2Productivity
If the automation controller is too aggressive and does not detect failure when failure actually occurs, then productivity is maintained, but reliability deteriorates as the mobile machine may be unable to complete its mission
Solution Approach 1:
Multiple stop trajectories are pre-computed at various points along the pathway, allowing the system to maintain productivity by seamlessly transitioning to alternative trajectories when failure occurs, rather than halting operations for recomputation.
Solution Approach 2:
The system continuously monitors sensor data quality and trajectory execution progress, providing feedback to the failure detection algorithm. This feedback mechanism enables the controller to distinguish between temporary disturbances and actual failures, ensuring reliable detection without unnecessary interruptions to mission completion.
3Reliability
If the automation controller uses complex failure detection algorithms, then reliability is improved, but device complexity increases
Solution Approach 1:
Stop trajectories are pre-computed and stored in memory before failure occurs. This preliminary action simplifies the real-time control system, as the complex computational task of trajectory generation is shifted to the planning phase, reducing the complexity of the failure detection and response mechanisms.
Solution Approach 2:
The control system is segmented into distinct functional modules: trajectory planning, failure detection, and execution control. Each module operates independently with well-defined interfaces, reducing overall system complexity while maintaining high reliability through specialized optimization of each component.
4Reliability
If the automation controller stops the mobile machine frequently to ensure safety, then reliability is improved, but loss of time increases due to unnecessary stops
Solution Approach 1:
Multiple stop trajectories are pre-computed at different locations along the pathway. When failure is detected, the controller selects the most appropriate pre-computed trajectory based on current position and conditions, enabling safe stopping without time loss to recomputation or suboptimal stopping locations.
Solution Approach 2:
The system continuously evaluates sensor data quality and trajectory execution progress to provide feedback on actual system state. This feedback enables intelligent discrimination between genuine failures requiring stops and temporary disturbances that can be tolerated, reducing unnecessary stops while maintaining safety.
Data Source
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AI summary
In an embodiment, an automation controller periodically generates stop trajectories and controls actuators to follow the stop trajectories. As long as new stop trajectories continue to be generated, the automation controller may follow a destination trajectory that is formed from the first portion of each stop trajectory. If stop trajectories are not generated for a period of time (e.g., due to failure in one or more computers generating the stop trajectories), the automation controller may continue to follow the most recent stop trajectory and bring the mobile machine to a stop.