Forklift Remote Operation With Vision-Guided Pallet Positioning
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Solution Overview
Problem
Operators face difficulties in moving a forklift truck to the precise position of a pallet and inserting the fork into pallet holes when using a remote operation system with a camera, as it is time-consuming and challenging to navigate accurately by watching the screen.
Innovation Solution
A forklift-truck remote operation system that includes a camera on the forklift truck for image capture, a display for image viewing, a pallet detector for image recognition, and a travel controller to automatically move the forklift to the selected pallet, with features like pop-up boxes or highlighted outlines for easy selection and automatic fork insertion.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If remote operation with camera is used, then operator safety is improved, but positioning accuracy deteriorates
Solution Approach 1:
The patent introduces an automated vision system as an intermediary between the operator and the forklift positioning task. The camera captures images of pallets, the recognition unit identifies pallet positions and orientations, and the travel control unit automatically navigates the forklift to the target position, eliminating the need for manual visual positioning while maintaining operator safety through remote operation.
Solution Approach 2:
The patent replaces the manual mechanical positioning system (operator visually guiding the forklift) with an automated optical-mechanical system. The camera-based vision system detects pallet positions, and the automated travel control system executes precise positioning, substituting human visual-motor coordination with machine-based optical detection and automated control.
2Device complexity
If manual remote operation is used, then device complexity is reduced, but operation time increases
Solution Approach 1:
The system performs preliminary actions by automatically capturing images of the workspace, recognizing pallet positions and orientations before the forklift arrives, and pre-calculating the optimal travel path. This preliminary processing of visual information and positioning data eliminates the need for time-consuming manual scanning and positioning adjustments during actual operation.
Solution Approach 2:
The forklift system performs self-service through automated functions: the camera autonomously captures workspace images, the recognition unit automatically identifies pallet positions and orientations, and the travel control unit self-navigates the forklift to the target position without continuous manual intervention, significantly reducing operation time while maintaining reasonable system complexity.
Data Source
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AI summary
Provided is a remote operation system for forklift comprising a forklift (20) and a remote operation device (40). The system comprises: a camera (33) which is attached to the forklift (20) and is for capturing an image of the surroundings of the forklift (20); a display unit (44) which is disposed on the remote operation device (40) and is for displaying the image captured with the camera (33); and a control unit (42). The control unit (42) detects a plurality of pallets by carrying out an image recognition process on the image captured with the camera (33). When the display unit (44) displays the image captured with the camera (33), the control unit (42) causes a display to be carried out for selecting the detected pallet. The control unit (42) causes the forklift (20) to move to the position of the selected pallet.