Forklift Stowage Position Detection Using Point Cloud Edge Analysis
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Solution Overview
Problem
Existing forklifts face challenges in stowing cargo on loading surfaces with objects already mounted, as they struggle to detect suitable stowage positions without interfering with existing objects.
Innovation Solution
A forklift equipped with an external sensor and processing circuitry that uses point clouds to detect the loading platform, extract horizontal planes, edges, and mounted objects, and calculates a stowage position separated from existing objects by a prescribed distance along the edge of the platform.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the forklift uses a simple height detection method to detect the loading surface, then the detection system is simple and fast, but it cannot identify objects already mounted on the loading surface, leading to potential collisions or improper stowage
Solution Approach 1:
The patent transitions from one-dimensional height detection to three-dimensional point cloud detection. By using an external sensor to capture spatial coordinates (x, y, z) of multiple points, the system can not only detect the loading surface height but also identify objects mounted on it through spatial analysis of the point cloud data, resolving the contradiction between detection precision and system complexity
Solution Approach 2:
The patent segments the point cloud data into different components: loading surface points, object points, and edge points. By applying clustering algorithms and spatial analysis to divide and categorize the detected points, the system can simultaneously identify the loading surface height and detect mounted objects, achieving high measurement precision through systematic data segmentation
2Productivity
If the forklift detects only the loading surface height without identifying mounted objects, then the stowage process is fast and simple, but the cargo may collide with or improperly overlap existing objects on the loading surface
Solution Approach 1:
The patent performs preliminary detection of the loading environment using the external sensor before the stowage operation begins. By capturing the point cloud data and identifying object positions in advance, the system can plan a safe stowage trajectory that avoids collisions, ensuring reliability while maintaining operational efficiency through advance preparation
Solution Approach 2:
The patent uses real-time feedback from the external sensor to monitor the forklift's position and the loading surface environment during the stowage operation. The control unit continuously processes point cloud data to detect mounted objects and adjusts the stowage trajectory dynamically, ensuring safe operation while maintaining productivity through adaptive control
3Reliability
If the forklift uses a comprehensive point cloud analysis method to detect both loading surface and mounted objects, then stowage safety is improved, but the processing time and computational complexity increase
Solution Approach 1:
The patent segments the point cloud processing into distinct stages: initial scanning to identify the loading surface plane, subsequent analysis to detect objects above the plane, and final calculation of the stowage position. This segmented approach reduces computational complexity at each stage while maintaining overall detection accuracy and reliability
Solution Approach 2:
The patent applies partial action by focusing computational resources on critical detection tasks: first establishing the loading surface plane equation, then only analyzing points above this plane for object detection. This selective processing approach maintains high stowage position accuracy while minimizing unnecessary computational overhead and processing time
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 the forklift to autonomously detect and avoid existing objects on the loading surface, ensuring safe and efficient stowage of cargo without interference, even when the parking position and orientation of the truck are unknown.
Implementation Method 1
an external sensor that detects a position of an object, the position of the object being represented by a point cloud that is a set of points expressed by coordinates in a three-dimensional coordinate system
Data Source
AI summary
A forklift stows a cargo on a loading surface. The loading surface is an upper surface of a loading platform. The forklift includes an external sensor configured to detect a position of an object, and processing circuitry. The position of the object is represented by a point cloud that is a set of points. The processing circuitry is configured to extract points that represent the loading platform, extract, from the points that represent the loading platform, points that represent an edge of the loading platform, detect a straight line that represents the edge from the points representing the edge, extract points that represent an object mounted on the loading platform, and detect, as a stowage position on which the cargo will be stowed, a position that is separated from the mounted object by a prescribed distance in a direction in which the straight line extends.