RF-LIDAR Hybrid Positioning for Underground Mining
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Solution Overview
Problem
Existing positioning systems for underground mining environments, such as LIDAR, face challenges in accurately determining the location of machines due to non-unique shapes and the absence of permanent objects, leading to difficulties in correlating scanned data with pre-existing maps.
Innovation Solution
A positioning system that combines optical sensing with radio frequency signals using a controller, optical sensing device, and signal devices to generate shape data and determine the machine's position by correlating it with reference shape data, and employs a particle filter simulation to refine the location accuracy in environments with similar features.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If LIDAR systems are used to determine machine location by scanning shapes, then position information can be obtained, but the system fails when shapes are not unique to specific locations or when permanent objects are absent
Solution Approach 1:
The patent combines LIDAR shape scanning with radio frequency signal transmission to create a hybrid positioning system. The LIDAR provides shape data while RF signals provide distance measurements, and the controller integrates both data sources to determine position, thereby overcoming the limitations of using either system alone in underground mining environments
Solution Approach 2:
The controller acts as an intermediary that receives shape data from the LIDAR and distance information from RF signal exchanges, then correlates these data with stored map information to infer machine position. This intermediary processing resolves the contradiction by synthesizing multiple data sources rather than relying on shape matching alone
2Adaptability or versatility
If LIDAR systems rely on matching scanned shapes to pre-existing maps, then location can be inferred, but the system cannot handle newly added objects or non-unique shapes
Solution Approach 1:
The patent adds a new dimension of measurement by incorporating radio frequency distance measurements alongside LIDAR shape data. This additional dimensional information (distance via RF signals) allows the system to disambiguate locations with similar shapes and adapt to new objects without requiring exact shape matches in pre-existing maps
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
This system enables high-precision position determination of machines in underground mining environments by overcoming the limitations of LIDAR systems, providing accurate location data even in areas with similar shapes and non-permanent objects.
Implementation Method 1
a first signal device configured to transmit a radio frequency signal and receive a response signal
Implementation Method 2
an optical sensing device configured to generate determined shape data associated with a portion of the worksite at the position of the machine
Data Source
AI summary
A positioning system and method for determining a position of a machine are disclosed. The system may have an optical sensing device configured to generate determined shape data associated with a portion of the worksite at the position of the machine. The system may have a first signal device configured to transmit a radio frequency signal and receive a response signal. The system may have a second signal configured to receive the transmitted radio frequency signal and transmit the response signal. The system may have a controller in communication with the optical sensing device and at least one of the first and second signal devices. The controller may be configured to determine an approximate position based on the radio frequency signal and the response signal, identify a reference shape data corresponding to the determined shape data, and determine the position based on the approximate position and the reference shape data.