Optical Marker Localization for GNSS-Denied Working Machines

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Solution Overview

Problem

Existing GNSS-based machine localization systems for off-highway working vehicles are costly, complex to set up and maintain, and dependent on accurate satellite reception, which can be compromised by weather or geographic conditions, leading to reduced precision and safety issues during work tasks.

Innovation Solution

A machine localization system using low-cost GNSS receiver circuitry and perception sensors like LiDAR and IR markers with machine-readable optical images, allowing the working machine to determine its position and navigate autonomously even in low GNSS accuracy conditions, by creating a landmark map and fusing sensor data for high-confidence localization.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If GNSS-based machine localization systems are used, then navigation capability is provided, but cost and system complexity increase

Engineering Contradiction:

Improvenavigation reliabilityVSAvoidsystem complexity

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The system segments the localization task into multiple components: GNSS receiver for coarse positioning, perception sensors for environmental feature detection, and a landmark map for reference. This segmentation allows each component to operate independently with optimized complexity, reducing overall system complexity while maintaining navigation reliability.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent introduces a landmark map as an intermediary between the GNSS system and the working machine. The landmark map stores pre-surveyed environmental features and serves as a reference for correcting GNSS positions, especially in GNSS-denied environments. This intermediary enables the system to maintain navigation reliability without directly relying on complex GNSS infrastructure.

Inventive Principle:

Principle #24Intermediary (Mediator)

2Measurement precision

If GNSS-based localization is used, then position determination is achieved, but precision decreases under adverse weather or geographic conditions

Engineering Contradiction:

Improvepositioning precisionVSAvoidweather and geographic interference

Core Design Contradiction:

Measurement precisionVSObject-affected harmful factors

Solution Approach 1:

The system performs pre-surveying of the work area to create a landmark map containing environmental features before actual work begins. This beforehand preparation creates a reference framework that cushions against GNSS signal degradation during work operations. When GNSS precision decreases due to weather or geographic conditions, the pre-established landmark map provides a stable reference for position correction.

Inventive Principle:

Principle #11Beforehand cushioning (Prior cushioning)

Solution Approach 2:

The system continuously compares real-time sensor data with the pre-surveyed landmark map to correct GNSS position estimates. This feedback mechanism allows the system to detect and compensate for GNSS errors caused by adverse conditions, maintaining positioning precision even when GNSS signals are compromised by weather or geographic interference.

Inventive Principle:

Principle #23Feedback

3Productivity

If autonomous navigation is implemented, then operational efficiency improves, but dependency on accurate GNSS signals increases

Engineering Contradiction:

Improveoperational efficiencyVSAvoidsignal dependency

Core Design Contradiction:

ProductivityVSReliability

Solution Approach 1:

The system performs preliminary surveying of the work area to create a comprehensive landmark map before autonomous operations begin. This preliminary action establishes a complete reference framework of environmental features that enables autonomous navigation without continuous reliance on accurate GNSS signals. The pre-captured environmental data allows the working machine to navigate autonomously even when GNSS signals are unavailable or inaccurate.

Inventive Principle:

Principle #10Preliminary action

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

Enables reliable and efficient autonomous navigation and task performance in various weather conditions and environments without relying solely on GNSS, reducing operational costs and improving precision and safety.

Implementation Method 1

perception sensors (e.g., LiDAR, camera, radar)

Methodology Applied

Scientific EffectLIDAR: LIDAR

Implementation Method 2

IR markers with machine-readable optical images

Methodology Applied

Scientific EffectInfrared radiation: Infrared Radiation

Data Source

PatentUS20240057501A1Machine readable optical images for GNSS-denied navigation and localization of a working machine

Publication Date: 2024.02.22 KUBOTA CORP

AI summary

Some embodiments may include a working machine to perform one or more work tasks in a work area, the working machine comprising: a machine localization system to localize the working machine based on perception sensor observations indicative of data embedded on one or more markers placed in the work area or proximate to the work area, wherein the working machine obtains localization data responsive to reading one or more machine-readable optical images on the one or more markers, respectively, wherein the working machine determines, using the obtained localization data, an absolute position of the working machine or one or more absolute positons of the one or more markers, respectively; and wherein the working machine performs the one or more work tasks based on the determined absolution position(s). Other embodiments may be disclosed and/or claimed.