Agricultural Vehicle Guidance for Hidden 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, disrupt service, and increase operational costs, while also posing safety hazards from reduced visibility.
Innovation Solution
A guidance system for agricultural vehicles that uses image sensors and GNSS data to identify and classify objects, generate geospatial maps, and adjust vehicle operations automatically to avoid obstacles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If roadside mowing operations are conducted to maintain clear visibility, then driver safety and general upkeep are improved, but equipment damage risk and operational costs increase due to hidden obstacles
Solution Approach 1:
The system performs preliminary detection of obstacles (telecom boxes, power boxes, rocks, debris) before mowing operations begin. By scanning the area ahead and mapping obstacle locations in advance, the system allows the vehicle to navigate around hazards before they become problematic, preventing equipment damage while maintaining the safety benefit of clear roadside vegetation.
Solution Approach 2:
The system introduces an intermediary detection and mapping layer between the mowing equipment and hidden obstacles. Sensors detect obstacles, the processor creates a geospatial map, and this intermediate information guide the vehicle navigation, preventing direct contact between mowing equipment and obstacles that would cause damage.
2Illumination intensity
If frequent mowing cycles are implemented to manage fast-growing vegetation, then visibility is maintained, but operational costs increase significantly
Solution Approach 1:
The system performs preliminary obstacle mapping before mowing operations. By detecting and recording obstacle locations in advance, the system enables more efficient mowing routes that avoid repeated stops and maneuvers around hidden hazards, reducing overall operational time and costs while maintaining vegetation management effectiveness for visibility.
Solution Approach 2:
The system provides real-time feedback to the operator about detected obstacles and recommended navigation adjustments. This feedback loop allows operators to optimize mowing routes dynamically, avoiding areas with hidden obstacles that would require slow, careful navigation, thereby reducing operational costs while maintaining effective vegetation control.
3Reliability
If manual obstacle detection is used during mowing operations, then equipment damage can be prevented, but operator safety is compromised due to reduced visibility
Solution Approach 1:
The system replaces manual visual detection by the operator with automated sensor-based detection. Sensors scan the environment ahead of the vehicle, detecting obstacles that would be invisible to the operator through dense vegetation. This substitution protects equipment from damage while the operator maintains clear visibility and focus on the mowing task without needing to constantly scan for hidden hazards.
Data Source
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 pieces of refuse depicted within the image data, receive GNSS location data, responsive to identifying and classifying one or more pieces of refuse, log location data indicating locations of the one or more pieces of refuse, 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 pieces of refuse on the geospatial map.