Load Handling Vehicle Localization With Synchronized LiDAR and Camera Mapping
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Solution Overview
Problem
Localization of load handling vehicles in uncertain or uncontrolled environments is challenging, particularly in navigating safely to a load target with potential large uncertainties in target position.
Innovation Solution
A controller system that obtains spatial maps and uses synchronized sensor signals from LiDAR and camera systems to localize both the vehicle and load target, mitigating errors and uncertainties, and plans trajectories for safe navigation and loading/unloading.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If localization is performed in moving or uncertain coordinate frames, then the system can adapt to vehicle motion, but error accumulation increases and localization precision deteriorates
Solution Approach 1:
Instead of transforming map coordinates to moving vehicle coordinates (conventional approach), the patent inverts the approach by transforming sensor data into a fixed spatial map coordinate system. The vehicle's position is determined by matching sensor data to the fixed map, eliminating error accumulation from continuous coordinate transformations while maintaining adaptability to vehicle motion.
2Measurement precision
If multiple sensor systems are used to improve localization accuracy, then measurement precision improves, but device complexity increases
Solution Approach 1:
The patent merges data from multiple sensor systems (LiDAR, cameras, GPS, IMU) into a unified localization framework that operates within a single fixed spatial map coordinate system. This integration approach improves localization accuracy by combining complementary sensor information while managing complexity through a cohesive processing architecture rather than separate independent systems.
Solution Approach 2:
The fixed spatial map serves as an intermediary reference frame that mediates between different sensor systems and the vehicle's navigation system. All sensor data is transformed into this common fixed coordinate system, which acts as a stable mediator eliminating the need for complex real-time transformations between moving coordinate frames and reducing overall system complexity.
3Reliability
If synchronized sensor data from multiple sources is processed, then localization reliability improves, but computational requirements and processing time increase
Solution Approach 1:
The spatial map is pre-computed and stored in a fixed coordinate system before the vehicle reaches the location. This preliminary preparation of the reference framework eliminates the need for complex real-time computations during vehicle operation, allowing synchronized sensor data to be quickly matched against the pre-existing fixed map for reliable and efficient localization.
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 enhances the accuracy and reliability of load handling operations, improving safety and productivity by providing precise localization and path planning, even in uncertain environments, and reduces the need for skilled drivers.
Implementation Method 1
receive first sensor signals from a first sensor system for generating point clouds of the surrounding of the load handling vehicle
Implementation Method 2
receive second sensor signals from a second sensor system for generating images of the surrounding of the load handling vehicle
Data Source
AI summary
Disclosed is a load handling controller and a method for localizing a load handling vehicle and a load target. A spatial map describing a surrounding of the load handling vehicle is obtained. First sensor signals are received from a first sensor system for generating point clouds of the surrounding of the load handling vehicle and second sensor signals are received from a second sensor system for generating images of the surrounding of the load handling vehicle. The second sensor signals are synchronized in time with the first sensor signals. The load handling vehicle and the load target are localized in the spatial map based on the first sensor signals and the second sensor signals.