Optical Target Localization for Indoor Vehicle Navigation Gaps
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Solution Overview
Problem
Industrial vehicles in warehouses face challenges in navigation and localization, particularly in environments with insufficient overhead features or when transitioning between mapped areas, leading to potential loss of localization and reduced accuracy.
Innovation Solution
The implementation of a system that uses a camera and vehicular processor to capture and analyze overhead features, match them with a warehouse map, filter and decode optical targets, calculate vehicle pose, and navigate the vehicle using a combination of optical targets and other localization methods to ensure accurate tracking and re-localization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the vehicle uses overhead features for localization, then navigation accuracy is improved, but the system fails in areas with insufficient overhead features
Solution Approach 1:
The system pre-registers optical targets at known locations in the warehouse before operation. These targets are positioned in advance and their coordinates are stored in the map data, allowing the vehicle to quickly acquire localization information when passing through these pre-prepared locations, solving the problem of insufficient overhead features in real-time.
Solution Approach 2:
Optical targets serve as intermediary objects between the vehicle's localization system and the warehouse environment. These targets are specifically designed with high-contrast patterns and known geometries that make them easily detectable by the vehicle's camera system, acting as reliable mediators for position determination even when other overhead features are scarce.
2Area of stationary object
If the vehicle transitions between mapped areas, then coverage is improved, but localization is lost at boundaries
Solution Approach 1:
The system extends localization from two-dimensional overhead feature recognition to three-dimensional space by incorporating vertically mounted optical targets. The vehicle's camera system captures these targets and uses their known three-dimensional positions and orientations to calculate accurate vehicle pose, providing continuous localization across area boundaries by adding a vertical dimension to the feature space.
3Reliability
If the system uses multiple localization methods, then reliability is improved, but system complexity increases
Solution Approach 1:
The localization system is segmented into distinct functional modules: optical target detection module, feature matching module, pose calculation module, and navigation control module. Each module performs a specific function and can be independently optimized or replaced, reducing overall system complexity while maintaining high reliability through modular architecture.
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 solution enables accurate and reliable navigation and tracking of industrial vehicles within warehouses, even in areas with limited features, by utilizing optical targets to determine vehicle pose and maintain localization, thereby enhancing operational efficiency and accuracy.
Implementation Method 1
The camera may be communicatively coupled to the vehicular processor and captures an input image of overhead features
Data Source
AI summary
Vehicles, systems, and methods for navigating or tracking the navigation of a materials handling vehicle along a surface that may include a camera and vehicle functions to match two-dimensional image information from camera data associated with the input image of overhead features with a plurality of global target locations of a warehouse map to generate a plurality of candidate optical targets, an optical target associated with each global target location and a code; filter the targets to determine a candidate optical target; decode the target to identify the associated code; identify an optical target associated with the identified code; determine a camera metric relative to the identified optical target and the position and orientation of the identified optical target in the warehouse map; calculate a vehicle pose based on the camera metric; and navigate the materials handling vehicle utilizing the vehicle pose.