Agricultural Implement Perception Control for Configuration Changes
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Solution Overview
Problem
Existing agricultural vehicle perception systems fail to adapt to changes in agricultural vehicles or implements, ignoring features like terrain and other implements, leading to inefficient operation and potential false obstacle detection.
Innovation Solution
A controller refinement system with a processor that evaluates sensor data to recognize changes in agricultural implement configuration, selects appropriate sensor profiles, and adjusts steering and propulsion parameters to manage new implements, providing predictive maintenance and enhanced control.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If sensors are configured to ignore features like implement or vehicle to decrease false positive detection, then false obstacle detection is reduced, but the system becomes unable to detect actual changes in implement configuration
Solution Approach 1:
The system divides the monitoring task into two segments: the original controller continues to ignore the implement/vehicle for obstacle detection purposes, while a refinement controller specifically monitors for implement configuration changes. This segmentation allows each controller to specialize in its function without interference.
Solution Approach 2:
The refinement controller acts as an intermediary between the sensors and the original controller. It receives sensor data, identifies implement configuration changes, and communicates these changes back to the original controller, which then adjusts its obstacle detection parameters accordingly.
2Device complexity
If a fixed configuration perception system is used, then system complexity is reduced, but the system cannot adapt to changes in agricultural vehicles or implements
Solution Approach 1:
The system transitions from a static, fixed configuration to a dynamic one where the refinement controller continuously monitors sensor data and automatically adjusts the sensor profile based on detected implement changes. This dynamic adaptation maintains operational effectiveness without requiring manual reconfiguration.
Solution Approach 2:
The refinement controller enables the perception system to self-adjust and self-optimize by automatically detecting implement configuration changes and selecting appropriate sensor profiles without external intervention, maintaining adaptability while keeping the overall system architecture relatively simple.
3Device complexity
If existing sensors and controllers are used for their initial purposes, then system simplicity is maintained, but enhanced functionality for new implements is not available
Solution Approach 1:
The refinement controller serves multiple functions: it monitors implement configuration, identifies changes, selects appropriate sensor profiles, and communicates with the original controller. This multi-functionality enhances system capabilities without requiring separate specialized systems for each function.
Solution Approach 2:
The refinement controller is integrated with the existing sensor array and original controller, merging monitoring and control functions into a unified system. This combination leverages existing hardware resources while adding intelligent adaptation capabilities through software-based control.
Data Source
AI summary
The present disclosure relates to a system configured to enhance the monitoring and control of agricultural equipment, particularly when different tools or implements are attached to an agricultural vehicle such as a tractor. In examples, this system is equipped with sensors that detect changes in the equipment's configuration, such as when implements are swapped or adjusted. Upon recognizing these changes, the system selects an appropriate sensor profile to effectively monitor the tool and the environment surrounding the agricultural vehicle and the agricultural implement. Monitoring the agricultural system allows for real-time adjustments to the vehicle's steering and operational functions, ensuring optimal performance. Additionally, the system alerts the operator if manual intervention is needed and autonomously adapt to new configurations, which may include compensating for wear or misalignment of the implements, according to examples.