Agricultural Vehicle Guidance for Detecting and Avoiding Roadside Obstacles

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Solution Overview

Problem

Challenges exist in roadside mowing operations due to hidden obstacles like telecom and power boxes, which can damage equipment, disrupt services, and increase operational costs, while overgrown vegetation reduces visibility and poses safety hazards.

Innovation Solution

A guidance system for agricultural vehicles equipped with image sensors and GNSS technology to identify and classify objects, adjusting operations to avoid obstacles and log locations, including automatic disengagement of power take-out controls and hydraulic valve actuation to modify implement orientation.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If roadside mowing operations are conducted to maintain clear visibility, then driver safety and visibility are improved, but the risk of damage to mowing equipment and infrastructure increases

Engineering Contradiction:

Improvedriver safetyVSAvoidequipment damage risk

Core Design Contradiction:

ReliabilityVSObject-affected harmful factors

Solution Approach 1:

The system performs preliminary detection of obstacles such as telecom boxes, power boxes, and water wells before the mowing operation reaches them. By identifying these objects in advance using image sensors and GNSS positioning, the system can prepare appropriate avoidance actions, thereby maintaining safety while preventing equipment damage.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system continuously monitors the environment during mowing operations using image sensors that capture real-time data. This feedback loop allows the system to detect obstacles, determine their locations, and adjust the mowing path dynamically, ensuring both visibility maintenance and equipment protection.

Inventive Principle:

Principle #23Feedback

2Reliability

If frequent mowing cycles are implemented to manage fast-growing vegetation, then roadside appearance and safety are improved, but operational costs increase

Engineering Contradiction:

Improveroadside safetyVSAvoidoperational costs

Core Design Contradiction:

ReliabilityVSLoss of energy

Solution Approach 1:

The system logs the locations of detected infrastructure objects such as water wells, telecom boxes, and power boxes. This creates a persistent database that can be used in subsequent mowing operations, eliminating the need for repeated detection and allowing for more efficient, targeted mowing cycles that reduce overall operational costs while maintaining safety.

Inventive Principle:

Principle #10Preliminary action

3Measurement precision

If manual monitoring of roadside vegetation is performed, then obstacle detection accuracy is improved, but time consumption and labor costs increase

Engineering Contradiction:

Improveobstacle detection accuracyVSAvoiddetection time

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The system replaces manual monitoring with automated image sensors that capture visual data of the roadside environment. These sensors, combined with machine learning algorithms, automatically identify and classify obstacles such as telecom boxes, power boxes, and water wells, providing accurate detection without human intervention and significantly reducing time consumption.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The system performs self-detection and self-classification of obstacles using onboard image sensors and processing units. The agricultural vehicle autonomously identifies objects of interest, determines their locations using GNSS data, and logs this information without requiring external manual monitoring, thereby achieving both accuracy and efficiency.

Inventive Principle:

Principle #25Self-service

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

Enhances safety by avoiding damage to equipment and infrastructure, reduces operational costs through efficient mowing, and improves visibility by detecting and classifying objects like water wells and vegetation.

Implementation Method 1

receive image data from an image sensor

Methodology Applied

Scientific EffectLight detection: Photoelectric Effect

Implementation Method 2

The image sensor may include at least one of a thermal camera

Methodology Applied

Scientific EffectThermal radiation detection: Thermal Radiation

Implementation Method 3

a light detection and ranging (LIDAR) camera

Methodology Applied

Scientific EffectLIDAR: LIDAR

Implementation Method 4

receive GNSS location data

Methodology Applied

Scientific EffectSatellite signal detection: Radar

Data Source

PatentUS20260026421A1Object Detection, Recording, and Avoidance System, Agricultural Vehicle Include the Object Detection, Recording, and Avoidance System, and Related Methods

Publication Date: 2026.01.29 AGCO INT GMBH

AI summary

A guidance system for controlling operation of an agricultural vehicle. The guidance system includes at least one processor and at least one non-transitory computer-readable storage medium storing instructions thereon that, when executed by the at least one processor, cause the guidance system, during an agricultural operation, to: receive image data from an image sensor, analyze the image data to identify and classify one or more water wells depicted within the image data, receive GNSS location data, and responsive to identifying and classifying one or more water wells, log location data indicating locations of the one or more water wells.