Autonomous Dozing Missed Cut Detection and Reaction
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Solution Overview
Problem
Conventional autonomous dozing systems lack effective means to react to missed cuts, leading to inefficiencies and reduced productivity due to compounded deviations from the planned cut profile, especially in environments with material inconsistencies and irregular work surfaces.
Innovation Solution
A computer-implemented method and control system that identifies missed cuts based on implement position and target cut points, predicts performance values considering implement load, and restarts the pass if the performance is below a threshold and the load is sufficient, using a controller with modules for detection, prediction, and reaction to optimize productivity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If conventional autonomous dozing systems use sensors to monitor cut position and adjust blade position, then manufacturing precision of cut is improved, but the system lacks the ability to react to missed cuts, reducing productivity
Solution Approach 1:
The system continuously monitors actual cut position against target cut points using sensors, calculates deviations, and provides feedback to the control system. When a missed cut is detected, the system calculates performance values and provides feedback on whether to restart the pass, creating a closed-loop control system that reacts to deviations.
Solution Approach 2:
The system predicts performance values before executing the restart decision. By calculating the performance value in advance based on the missed cut and implement load, the system determines whether restarting will improve overall efficiency, allowing proactive correction rather than reactive adjustment.
2Manufacturing precision
If the system restarts the pass after a missed cut, then manufacturing precision is improved, but time is lost due to restarting
Solution Approach 1:
The system changes the decision parameter from simple missed cut detection to a performance value calculation that incorporates implement load. By evaluating whether the performance value indicates insufficient load, the system intelligently decides when restarting is worthwhile, balancing precision improvement against time loss.
Solution Approach 2:
The system applies partial correction by not always restarting the pass. Instead of automatically restarting every missed cut, the system selectively restarts only when the performance value indicates the implement is underloaded, accepting some imprecision when the missed cut has minimal impact on overall efficiency.
3Manufacturing precision
If the system continuously monitors and adjusts blade position, then manufacturing precision is improved, but device complexity increases
Solution Approach 1:
The control system is segmented into distinct functional modules: a missed cut detection module that identifies deviations, a performance prediction module that calculates performance values based on implement load, and a reaction module that decides whether to restart. This modular architecture manages complexity by dividing the control function into manageable, independent components.
Solution Approach 2:
The system performs self-diagnosis and self-correction by automatically detecting missed cuts, calculating performance values, and making restart decisions without operator intervention. The control system serves itself by monitoring its own performance and autonomously correcting deviations, reducing the need for complex external monitoring and manual adjustment mechanisms.
Data Source
AI summary
A computer-implemented method of responding to a missed cut during a pass made along a planned cut profile using an implement is provided. The computer-implemented method may include identifying the missed cut based at least partially on an implement position and a target cut point, predicting a performance value of the pass based at least partially on the missed cut and an implement load, and restarting the pass if the performance value is less than a minimum performance threshold and the implement load is less than a minimum load threshold.