Lidar and Radio Frequency Positioning for Underground Tracking
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing positioning systems for mobile objects in underground environments, such as Lidar systems, face challenges in accurately determining the location of machines due to non-unique shapes, computational intensity, and the presence of temporary or moving objects, leading to potential loss of tracking and the need for manual intervention.
Innovation Solution
A method and system that combines Lidar data with radio-frequency communication using ultra-wideband signals to determine the position of a machine by associating distance data from Lidar surveys with light-reflective points and using radio-frequency communication between known and mobile devices to enhance positioning accuracy and reduce reliance on pre-existing maps.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If Lidar systems are used to track machine location by comparing captured data with reference maps, then position determination is achieved, but the system becomes computationally intensive and slow in finding matching references
Solution Approach 1:
The patent introduces radio frequency signal devices as intermediary elements between the Lidar system and the reference map. These signal devices transmit positional information that acts as a mediator, allowing the system to determine machine location without performing computationally intensive comparisons between captured Lidar data and reference maps. The signal devices receive and process positional data, reducing the computational burden on the main system.
2Reliability
If Lidar systems rely solely on correlating captured data with pre-existing maps, then position tracking is maintained, but the system loses track when encountering non-unique shapes, temporary objects, or objects not in the map
Solution Approach 1:
The patent implements preliminary action by pre-positioning radio frequency signal devices at known locations throughout the worksite before operations begin. These signal devices are established in advance and continuously transmit their positional information. When the Lidar system encounters environments with non-unique shapes or temporary objects, it can fall back on the pre-established signal device positions to maintain tracking continuity without manual intervention.
3Reliability
If manual intervention is required to re-seed the positioning system when tracking is lost, then position tracking can be restored, but productivity is reduced due to operator downtime
Solution Approach 1:
The patent implements self-service by enabling the positioning system to automatically recover from tracking loss without operator intervention. When the Lidar system encounters difficulties in matching captured data with reference maps, it automatically utilizes the radio frequency signal device positions to re-establish tracking. The system serves itself by switching between Lidar-based positioning and signal device-based positioning as needed, eliminating the need for manual re-seeding and maintaining operational continuity.
4Reliability
If radio frequency communication is added to enhance positioning accuracy, then positioning reliability is improved, but device complexity increases
Solution Approach 1:
The patent applies segmentation by dividing the positioning system into distinct functional components: Lidar units for environmental scanning, radio frequency signal devices for positional reference, and a control system for integrating data. Each component operates independently with a specific function, and the control system combines their outputs. This modular segmentation allows the system to achieve high reliability through multiple independent positioning methods while managing complexity through clear functional separation.
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 approach enables precise and efficient determination of machine positions in underground environments, reducing the need for manual intervention and improving tracking accuracy by integrating Lidar data with radio-frequency communication, even in areas with non-unique shapes and temporary objects.
Implementation Method 1
determining input data from a Lidar survey by a Lidar unit on the machine. The input data is associated with distances between the Lidar unit and respective light-reflective points in the worksite
Implementation Method 2
communicating by a radio-frequency communication between a first signal device at a known location within the worksite and a second signal device located on the machine
Data Source
AI summary
A method for determining a position of a machine in a worksite is disclosed. The method may include determining, using a Lidar unit on the machine, input data. The input data may be associated with distances between the Lidar unit and respective light-reflective points in the worksite. The method may also include transmitting a radio-frequency communication between a first signal device at a known location within the worksite and a second signal device located on the machine. Further, the method may include determining position data for the machine based on at least the radio frequency communication. The method may also include determining a position of the machine based on the position data and the input data.