Autonomous Container Landing via Multi-Sensor Point Cloud Analysis
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Solution Overview
Problem
Current automation systems for container handling in the Landside Transfer Zone face challenges in accurately determining landing positions due to variability in non-standard chassis and equipment, lack of standardized landing points, and safety concerns, which existing sensor technologies do not fully address.
Innovation Solution
A method and system using multiple measurement points to generate accurate landing solutions by analyzing point clouds and determining the location and orientation of containers on target equipment, employing techniques such as local minima, model convolution, and sensors like cameras, LiDAR, and sonar to identify twistlocks and other features, allowing for autonomous container placement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If multiple measurement points and point cloud analysis are used to determine landing positions, then landing precision is improved, but system complexity and computational requirements increase
Solution Approach 1:
The patent segments the measurement process into multiple discrete measurement points that are collected sequentially or simultaneously. Each measurement point represents a specific coordinate on the landing surface, and these segmented points are then processed collectively to form a complete picture of the landing surface geometry, enabling precise determination of container placement positions.
Solution Approach 2:
The patent transitions from two-dimensional surface representations to three-dimensional point cloud analysis. By collecting measurement points with x, y, and z coordinates, the system creates a volumetric representation of the landing surface, allowing for more accurate determination of landing positions that accounts for surface irregularities and variations in height.
2Productivity
If automated container handling is implemented in the Landside Transfer Zone, then productivity is improved, but safety risks and operational challenges increase due to variability in non-standard equipment
Solution Approach 1:
The patent changes the approach from relying on standardized equipment parameters to measuring actual physical parameters of each piece of equipment. By using measurement devices to capture the real geometry and characteristics of non-standard chassis and landing surfaces, the system adapts to varying equipment parameters, enabling safe and accurate automated handling of diverse equipment types.
Solution Approach 2:
The patent implements a feedback mechanism where measurement data from the landing surface is fed back into the control system to adjust container placement decisions. The measurement devices continuously monitor the landing surface characteristics, and this information is used to modify the automated handling operations in real-time, ensuring safety and accuracy despite equipment variability.
3Object-affected harmful factors
If remote operation is used for container handling, then human safety is improved, but operational speed and responsiveness decrease
Solution Approach 1:
The patent enables the container handling system to perform certain functions autonomously without continuous human intervention. The automated system uses measurement data to independently determine landing positions, adjust placement parameters, and execute container transfer operations, thereby maintaining safety while improving operational speed and responsiveness.
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
The system provides more accurate and robust landing solutions, reducing human intervention and increasing efficiency by determining precise landing positions on diverse equipment types, enhancing automation in the Landside Transfer Zone and beyond.
Implementation Method 1
employing techniques such as local minima, model convolution, and sensors like cameras, LiDAR, and sonar to identify twistlocks and other features
Implementation Method 2
sensors like cameras, LiDAR, and sonar to identify twistlocks and other features
Implementation Method 3
sensors like cameras, LiDAR, and sonar to identify twistlocks and other features
Data Source
AI summary
Systems and methods of generating landing solutions for containers onto landing surfaces using multiple measurement points generated by a measuring device or multiple measuring devices are described. In particular, methods of analyzing the plurality of measurement and from the analysis of the data, determining the location and orientation, in the container handling equipment's frame of reference, of where to place a shipping container onto a landing surface present within the equipment's workspace are described. This location can then be used by the equipment's automation system to automatically place the shipping container onto the landing surface without the need for human input, or relatively little human interaction or input. The systems and methods are applicable to operating in a landside transfer zone as well as outside such zone, and as such would be applicable to install on any container handling equipment which can land containers on equipment from above.