Gripper Camera Positioning for Automated Crane Load Coupling
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Solution Overview
Problem
Conventional crane systems require continuous manual operation, leading to human error and limitations in capturing detailed geometric features of loads due to limited camera views, especially with drones, which impair image recognition accuracy.
Innovation Solution
Incorporating a gripper camera signal-connected to a control device to detect geometric features like the upper edge, gripping edge, and gripper plate, allowing semi- or fully automated control for precise coupling with the load using machine learning algorithms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual control is used for crane operation, then operational flexibility is maintained, but human error increases and productivity decreases
Solution Approach 1:
The crane system performs self-positioning and self-coupling operations by automatically detecting geometric features of the load and calculating relative positions, enabling the system to serve itself without continuous human intervention while maintaining high reliability through automated control
Solution Approach 2:
The system uses camera feedback to continuously monitor the relative position between the gripper and load geometric features, enabling real-time adjustments and automated control decisions that improve both reliability and productivity
2Ease of operation
If drones are used for load detection, then operational distance is increased, but image recognition accuracy deteriorates due to limited resolution
Solution Approach 1:
The gripper camera acts as an intermediary between the crane system and the load, providing high-resolution geometric feature detection at close range while the operator remains at a safe distance, thus resolving the contradiction between operational safety and measurement precision
Solution Approach 2:
The system transitions from aerial detection (drone) to close-range detection (gripper camera), changing the spatial dimension of observation to achieve both operator safety and high measurement precision simultaneously
3Loss of information
If cameras are mounted on the crane system, then overview detection is improved, but detailed geometric feature capture deteriorates due to limited field of view
Solution Approach 1:
The detection system is segmented into two functional parts: overview cameras mounted on the crane for general load position detection, and a gripper camera for detailed geometric feature capture, allowing each component to specialize in its optimal detection range
4Productivity
If fully automated control is implemented, then productivity increases, but system complexity increases
Solution Approach 1:
The control system replaces complex mechanical positioning operations with automated image processing and computational geometry algorithms, detecting geometric features and calculating relative positions to enable fully automated coupling operations
Data Source
Figure 1~1a
Figure 2~2a
Figure 3~3b
AI summary
1. Crane system (1) for lifting loads (2), preferably in the form of semi-trailers, wherein the crane system (1) comprises a lifting device (3) and a control unit for controlling the lifting device (3), and wherein the lifting device (3) comprises at least one gripper (4) for coupling the lifting device (3) with the load (2), wherein at least one gripper camera (5) connected to or capable of being connected to the control unit is arranged on the at least one gripper (4), and wherein the control unit is configured to detect at least one geometric feature (6), preferably an upper edge (7) and/or a gripping edge (8) and/or a gripper plate (9), of the load based on image data acquired by means of the at least one gripper camera (5), to calculate a relative position of the at least one gripper (4) to the at least one geometric feature (6), and to couple the lifting device (3) to the load (2) semi- or fully automatically based on the relative position. to head towards. (Fig. 1)