Autonomous Vehicle Steering Control With Velocity Regulation
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Solution Overview
Problem
Autonomous agricultural machines require robust navigation control systems to follow guidance paths accurately without operator oversight, as they must handle both reference heading and distance heading errors to maintain precise operation and avoid anomalies.
Innovation Solution
A controller system that generates control signals by combining reference heading and distance heading errors using a weighting algorithm with a hyperbolic tangent function, allowing the machine to adjust its velocity and steering to align with the guidance path, incorporating a skid-steer mechanism for navigation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If automated guidance is used to enable machines to follow designated paths, then operational precision is improved, but the system complexity increases requiring robust control systems
Solution Approach 1:
The control system is segmented into multiple independent modules: a guidance module that processes path information, an error calculation module that computes deviations, and a control signal generation module that produces actuator commands. This modular architecture manages system complexity while maintaining high operational precision through specialized function distribution.
Solution Approach 2:
The system implements continuous feedback by calculating guidance errors based on the difference between actual machine position and desired path position, then using this error information to generate corrective control signals. This closed-loop feedback mechanism ensures operational precision while the automated nature of the feedback reduces the need for operator oversight.
2Productivity
If full machine automation is implemented without operator oversight, then operational efficiency is improved, but the reliability requirement increases to handle anomalies
Solution Approach 1:
The control system is designed with preliminary error handling capabilities built into the control algorithm itself, which can detect and correct common guidance deviations before they become operational anomalies. This preliminary action approach allows full automation to operate efficiently while maintaining high reliability through proactive error management.
Solution Approach 2:
The automated control system performs self-monitoring and self-correction by continuously calculating guidance errors and adjusting control signals without external intervention. This self-service capability enables full automation to maintain both operational efficiency and reliability by independently handling routine anomalies.
3Manufacturing precision
If velocity regulation is added to the control system to address heading errors, then navigation precision is improved, but the control algorithm complexity increases
Solution Approach 1:
The velocity regulation function is merged with the existing guidance control algorithm into a unified control law. The control signals combine both directional correction (from guidance error) and velocity adjustment (from heading error) in a single integrated computation, improving navigation precision while avoiding the need for separate complex velocity control modules.
Solution Approach 2:
The control algorithm dynamically adjusts velocity as a controllable parameter based on heading error magnitude and direction. By treating velocity as an additional adjustable parameter within the existing control framework rather than a separate control loop, the system achieves improved navigation precision with minimal increase in overall algorithmic complexity.
Data Source
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AI summary
A mobile machine comprises a chassis, a plurality of ground-engaging elements, a plurality of actuators for driving movement of the ground-engaging elements, and a controller for controlling each of the actuators to cause the mobile machine to follow a guidance path along a ground surface. The controller is configured to generate a first set of control values for driving the machine according to a first heading based on a reference heading error of the machine, generate a second set of control values for driving the machine according to a second heading based on a distance heading error of the machine, generate a current machine velocity using a prescribed machine velocity, the reference heading error, and the distance heading error, and generate control signals for driving the machine by combining the first set of control values, the second set of control values, and the current machine velocity.