Autonomous Work Machine Exception Handling With Supervisor Feedback
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Solution Overview
Problem
Autonomous work machines, such as UGVs, face challenges in safely and efficiently interacting with their environment and operators, particularly in industries like agriculture and construction, where accurate exception handling is crucial to prevent damage or errors.
Innovation Solution
A computer-implemented method that includes detecting objects or machine health/job quality issues during missions, determining if action is required, selectively storing information, and communicating with supervisors to decide on continuing the mission or shutting down the machine.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the autonomous work machine halts motion upon detecting an object, then safety is improved, but productivity deteriorates due to mission interruption
Solution Approach 1:
The system implements a feedback loop where the robotic controller continuously monitors object detections, evaluates them against safety criteria, and adjusts machine operation accordingly. When an object is detected, the system communicates with a supervisor who provides guidance on whether to halt or continue, creating a closed-loop control system that balances safety and productivity dynamically
Solution Approach 2:
The system dynamically adapts its response to detected objects based on multiple factors including object classification, location, and supervisor input. Rather than a static halt-on-detection rule, the system flexibly adjusts between continuing operation and halting motion, allowing productivity to be maintained when safe and safety to be prioritized when necessary
2Reliability
If the autonomous work machine implements comprehensive exception handling with supervisor communication, then reliability is improved, but device complexity worsens
Solution Approach 1:
The supervisor acts as an intermediary between the autonomous work machine and the control system. When an exception is detected, the robotic controller communicates the situation to the supervisor, who then provides high-level guidance. This intermediary approach allows complex exception handling without requiring the machine itself to have overly complex decision-making capabilities
Solution Approach 2:
The exception handling system is segmented into distinct functional modules: object detection by sensors, classification by the robotic controller, communication with the supervisor, and execution of instructed actions. This segmentation allows each component to remain relatively simple while the overall system achieves high reliability through coordinated operation of these modular elements
Data Source
AI summary
A control system for an autonomous work machine includes a robotic controller, a position detection system coupled to the robotic controller, and a sensor coupled to the robotic controller and configured to provide a sensor signal. A controlled system is coupled to the robotic controller to receive control signals from the robotic controller. The robotic controller is configured to generate an event relative to an object in an environment around the autonomous work machine or a machine health/job quality issue, document the event, and store the documented event. The robotic controller is further configured to selectively generate a communication containing at least some information relative to the documented event to a supervisor and to receive user input from the supervisor and take responsive action based on the user input.