Underground Mining Machine Routing With Curvature-Reduced Paths
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Solution Overview
Problem
Existing autonomous driving systems for underground mining machines are prone to wear due to driver-generated steering corrections, and the routing is specific to each vehicle, limiting flexibility and efficiency.
Innovation Solution
A computer-implemented method generates a navigable machine path using a curvature reducing algorithm, constrained by a determined navigable area, to minimize unnecessary steering and wear, independent of driver inputs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If path recording is performed manually by a driver, then the route can be established, but driver-generated steering corrections cause increased machine wear and reduced efficiency
Solution Approach 1:
The system performs self-positioning by automatically comparing sensor-measured distances to surrounding obstacles with pre-stored map data, eliminating the need for manual driver steering corrections. The machine autonomously calculates its position and generates optimized paths without human intervention, thereby reducing wear while maintaining routing accuracy.
Solution Approach 2:
The patent replaces manual mechanical steering control with an automated navigation system that uses sensor data and map comparisons to generate and follow optimized paths. This substitution eliminates the mechanical wear caused by driver corrections while maintaining precise route following.
2Ease of operation
If driver manual control is used for path recording, then routing can be established, but the routing becomes specific to each vehicle, limiting flexibility
Solution Approach 1:
The system creates universal map representations of the underground environment that can be used by any mining machine equipped with compatible sensors. The centralized server stores and manages these maps, allowing multiple vehicles to access and use the same routing information, thereby enabling flexible and adaptable routing across different machines rather than vehicle-specific paths.
Solution Approach 2:
The patent introduces a centralized server as an intermediary that stores map representations and communicates routing information to multiple mining machines. This intermediary enables flexible routing by allowing any vehicle to access optimized paths generated by the server, rather than each vehicle maintaining its own recorded routes.
3Manufacturing precision
If frequent steering corrections are made during autonomous driving, then path following can be maintained, but machine wear increases and higher speeds cannot be achieved
Solution Approach 1:
The system performs preliminary positioning by comparing sensor data with pre-stored map representations before executing path following. This advance position determination allows the machine to maintain accurate paths with minimal steering corrections, enabling higher speeds without sacrificing path following accuracy.
Solution Approach 2:
The patent implements a feedback mechanism where sensors continuously measure distances to surrounding obstacles, and this data is compared with stored map information to determine current position and generate corrective steering commands only when necessary. This feedback-based approach maintains path accuracy while minimizing frequent steering corrections, thereby reducing wear and enabling higher speeds.
Data Source
Figure 1A~1B
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AI summary
The present disclosure relates to a computer-implemented method, computer program, computer-readable medium, and a system for routing of an underground mining machine (100) in an underground environment, where the machine isconfigured to be driven from a first location (A) to a second location (B) in the underground environment.When carrying out the computer-implemented method, measured distances are obtained to surrounding obstacles along a route from the first location (A) to the second location (B), and a representation of a navigable area (410) along the route from the first location (A) to the second location (B) is determined, wherein the navigable area is a tolerance area along the route from the first location (A) to the second location (B). A navigable machine path (800; 802) is generated from the first location (A) to the second location (B), the navigable machine path (800; 802) being constrained to the navigable area (410) and being generated by a curvature reducing algorithm.The machine (100) is routed in accordance with the navigable machine path (800; 802) during autonomous driving from the first location (A) to the second location (B).