Agricultural Vehicle Guidance for Roadside Obstacle Mapping
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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, pose safety hazards, and increase operational costs.
Innovation Solution
A guidance system for agricultural vehicles that uses image sensors and GNSS data to identify and classify traffic markers, generating geospatial maps to adjust vehicle operations and avoid obstacles automatically.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual mowing operations are performed along roadsides, then vegetation can be maintained and visibility can be improved, but hidden obstacles such as telecom and power boxes can damage equipment and increase operational costs
Solution Approach 1:
The system performs preliminary detection of obstacles using image sensors and LiDAR before the mowing operation begins. The guidance system creates a map of the environment and identifies telecom boxes, power boxes, and other obstacles in advance, allowing the vehicle to plan its path to avoid damage before encountering these objects during mowing operations
Solution Approach 2:
The patent introduces an intermediary guidance system that acts as a mediator between the mowing operation and the environment. This system uses sensors to detect obstacles and processes this information to generate guidance signals that steer the vehicle around hidden objects, preventing direct contact between the mowing equipment and vulnerable infrastructure
2Reliability
If frequent mowing cycles are implemented to manage fast-growing vegetation, then roadside appearance and safety can be maintained, but operational costs increase significantly
Solution Approach 1:
The system implements feedback by continuously monitoring the environment with sensors and adjusting the vehicle's path in real-time based on detected obstacles. The guidance system processes sensor data, compares it with the planned path, and provides corrective steering commands to avoid obstacles while maintaining mowing coverage, ensuring high-quality maintenance without unnecessary re-operations
Solution Approach 2:
The patent applies dynamics by making the mowing path adaptive rather than fixed. The guidance system dynamically adjusts the vehicle's trajectory based on real-time obstacle detection, allowing the mowing operation to flexibly navigate around obstacles while maintaining coverage of vegetated areas, thereby achieving maintenance goals in a single pass
3Reliability
If automated obstacle detection and path adjustment systems are implemented, then equipment safety and operational efficiency can be improved, but system complexity increases
Solution Approach 1:
The guidance system is designed with multi-functionality, using a single integrated platform that performs multiple tasks: obstacle detection using various sensors, path planning, real-time navigation, and data logging. This universal system handles diverse obstacle types (telecom boxes, power boxes, rocks, debris) and environmental conditions through a unified architecture, reducing overall system complexity compared to separate specialized systems for each function
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 and efficiency by avoiding damage to infrastructure and reducing maintenance costs through automated obstacle detection and path adjustment.
Implementation Method 1
receive image data from an image sensor, analyze the image data to identify and classify one or more traffic markers depicted within the image data
Implementation Method 2
receive GNSS location data, responsive to identifying and classifying one or more traffic markers, log location data indicating locations of the one or more traffic markers
Data Source
Figure 1
Figure 2A~2B
Figure 3A~3B
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 traffic markers depicted within the image data, receive GNSS location data, responsive to identifying and classifying one or more traffic markers, log location data indicating locations of the one or more traffic markers, and based at least partially on the image data and the logged location data, generate a geospatial map indicating locations of the one or more traffic markers on the geospatial map.