Autonomous Work Vehicle Obstacle Handling by Field Boundary
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Solution Overview
Problem
Conventional autonomous travel systems mistakenly identify objects outside the work region as obstacles, leading to unnecessary collision avoidance maneuvers that decrease work efficiency.
Innovation Solution
The system differentiates between detection targets inside and outside the work region, and within or outside the vehicle's control range, adjusting the treatment processes accordingly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the work vehicle performs collision avoidance control for all detected objects, then safety is improved, but work efficiency decreases due to unnecessary maneuvers
Solution Approach 1:
The detection space is segmented into multiple regions (first detection region closer to the vehicle, second detection region farther away). Objects in different regions receive different treatments: collision avoidance control for objects in the first region, and notification-only for objects in the second region. This segmentation resolves the contradiction by applying safety measures only where necessary while maintaining efficiency for distant objects.
Solution Approach 2:
Different quality levels of response are applied to different spatial locations. The system provides high-quality collision avoidance control for nearby objects and lower-quality notification for distant objects. This local differentiation allows the system to maintain safety for critical threats while avoiding unnecessary maneuvers for distant objects, thus resolving the efficiency-safety tradeoff.
2Measurement precision
If the detection range is extended to cover more area, then detection capability is improved, but false identification of obstacles increases
Solution Approach 1:
The detection range is divided into two segments: a first detection region for nearby objects and a second detection region for distant objects. This segmentation allows the system to maintain extended detection capability while improving identification accuracy by treating different regions differently and applying appropriate response levels to each.
Solution Approach 2:
The system applies different quality levels of obstacle identification and response based on the local region. Objects in the first detection region receive full obstacle treatment with collision avoidance, while objects in the second region receive notification-only treatment. This local quality differentiation resolves the contradiction between extended detection range and accurate obstacle identification.
Data Source
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AI summary
[Problem] To provide a control method, a control program, and a control system capable of preventing a work efficiency from being decreased when a work vehicle detects a detection target during an autonomous travel. [Solution] An autonomous travel system (1) causes a work vehicle to execute treating processes different from each other depending on whether a detection target detected by an obstacle sensor (54) while the work vehicle (10) is autonomously traveling in a field is located inside the field or located outside the field.