Autonomous UGV Path Updating for Agricultural Obstacle Avoidance
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Solution Overview
Problem
Traditional agricultural machines rely heavily on manual operation, leading to inefficiencies and inconsistencies in agricultural processes, requiring improved automation to enhance productivity and resource utilization.
Innovation Solution
An unmanned ground vehicle (UGV) system equipped with motors, an obstacle sensor, and a processor that navigates based on pre-defined location information, detects obstacles, and updates its path to avoid them, enabling autonomous operation in agricultural settings.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual operation is used to control agricultural machines, then ease of operation is maintained, but productivity is low and quality is inconsistent
Solution Approach 1:
The UGV system performs agricultural tasks autonomously without continuous human intervention. The vehicle navigates automatically using GPS and pre-stored map data, detects obstacles using sensors, and executes agricultural operations independently, thereby eliminating the need for manual operation while significantly improving productivity and consistency
Solution Approach 2:
The patent replaces manual mechanical control with an automated control system comprising GPS receivers, microprocessors, sensors, and actuators. The system substitutes human operators with electronic navigation and control mechanisms that precalculate routes and automatically adjust vehicle movement and operational parameters
2Productivity
If autonomous navigation is implemented, then productivity increases and manual labor decreases, but device complexity increases
Solution Approach 1:
The UGV system integrates multiple functions into a single platform: navigation using GPS and stored maps, obstacle detection using various sensors, path recalculation, and agricultural task execution. This multi-functional integration achieves high productivity while managing complexity through consolidation rather than separate systems
Solution Approach 2:
The system performs preliminary actions by pre-storing geographic map data and precalculating navigation routes before field operations. This advance preparation enables autonomous navigation without real-time complex decision-making, reducing operational complexity while maintaining high productivity
3Reliability
If obstacle detection and path updating are implemented, then reliability of operation improves, but device complexity and processing requirements increase
Solution Approach 1:
The UGV system continuously monitors the environment using sensors to detect obstacles and compares detected positions with the planned navigation path. When obstacles are detected, the system provides feedback by recalculating the path and adjusting vehicle control in real-time, ensuring reliable safe operation through continuous closed-loop control
Solution Approach 2:
The navigation path is dynamically adjusted based on real-time obstacle detection. The system transitions from static pre-planned routes to dynamic adaptive navigation, continuously modifying the path to avoid obstacles while maintaining progress toward agricultural objectives, thereby ensuring reliable operation in changing environments
Data Source
AI summary
An unmanned ground vehicle (UGV) includes one or more motors configured to drive one or more wheels of the UGV, an obstacle sensor, a memory storing instructions, and a processor coupled to the one or more motors, the obstacle sensor, and the memory. The processor is configured to execute the instructions to cause the UGV to obtain location information of multiple navigation points; calculate a navigation path based on the obtained location information; drive the one or more motors to navigate the UGV along the navigation path; detect, by the obstacle sensor, whether one or more obstacles exist while navigating the UGV, and if detected, determine location information of the one or more obstacles; and if the one or more obstacles are detected by the obstacle sensor, update the navigation path based on determined location information of the one or more obstacles.