Feeding Machine Environment Monitoring for Sampling Front Obstacle Detection
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Solution Overview
Problem
Autonomous agricultural machines frequently experience unnecessary emergency stops due to product landslides or accumulations at the sampling front, requiring user intervention to restart the machine and clear the obstruction.
Innovation Solution
An environmental control process and system for autonomous animal feeding machines that utilize observation and processing means to detect potential obstacles, such as product accumulations, and alert the user, allowing for proactive intervention to prevent stops.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the autonomous agricultural machine is equipped with a safety device to detect obstacles, then safety is improved, but unnecessary emergency stops occur due to product landslides or accumulations being misinterpreted as obstacles
Solution Approach 1:
A camera is introduced as an intermediary device between the obstacle detection system and the safety stop mechanism. The camera captures images of the sampling front area, and image processing algorithms distinguish between actual obstacles (animals, persons, objects) and normal product conditions (landslides, accumulations). This intermediary visual verification system prevents misinterpretation by the safety device, allowing the machine to continue operating without unnecessary stops while maintaining safety for genuine obstacles.
2Productivity
If manual interventions are performed to remove product accumulations before sampling operations, then productivity is improved by preventing stops, but additional user time and effort are required
Solution Approach 1:
The system performs preliminary detection of product accumulations and landslides using the camera and image processing algorithms before the autonomous machine begins its sampling operations. By identifying potential obstacles in advance and distinguishing them from genuine safety hazards, the system allows operators to make informed decisions about whether intervention is necessary. This preliminary visual assessment reduces unnecessary manual clearing operations while preventing stops caused by actual obstacles.
3Productivity
If the autonomous machine performs multiple sampling passes to compose product mixture rations, then feeding operation completeness is improved, but exposure time to potential obstacles increases
Solution Approach 1:
The camera system continuously monitors the sampling front area during each sampling pass, providing real-time feedback about the presence of obstacles, animals, or product accumulations. This feedback loop allows the autonomous machine to adjust its operation dynamically - maintaining its sampling schedule to ensure feeding completeness while being alerted to genuine obstacles that require attention. The system distinguishes between temporary product conditions and persistent safety hazards.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This solution enables the user to anticipate and prevent emergency stops by removing potential obstacles, thereby improving the efficiency and productivity of the autonomous agricultural machine operations.
Implementation Method 1
observation means 1 on board the autonomous agricultural machine and configured so as to be able, at a position of the autonomous agricultural machine in front of the sampling front, to observe the environment of the autonomous agricultural machine in front of or at the sampling front
Data Source
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AI summary
[Method for controlling the environment of an autonomous agricultural animal feeding machine and environmental control system of such a machine. The present invention relates to a method for controlling the environment of an autonomous agricultural animal feeding machine (M) capable and intended, autonomously, during a sampling pass, to position itself in front of the sampling front (P1) of a pile of animal feed product (P) in a sampling position (N) and to perform a sampling operation on the sampling front (P1).The method consists, at each sampling pass, of performing, using an environmental monitoring system, an observation step of the environment of the autonomous agricultural machine (M) in front of or at the sampling front (P1), a processing step to deduce a positive critical detection result indicating the presence of at least one target, referred to as the critical target (C), likely to generate an incident at and/or in front of the sampling front (P1) during a subsequent sampling pass, or a negative critical detection result indicating the absence of critical target(s) (C), and a step to report the result. It also includes such a monitoring system enabling the implementation of said method.