AGV Pallet Loading Control for Precise Rear-Access Placement
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Solution Overview
Problem
Current automated systems for loading and unloading palletized goods into trucks or containers face inefficiencies, particularly when entering from the rear, as they require specialized equipment and infrastructure, and struggle with precise placement of pallets next to each other, often resulting in stuck loads and damage to transport surfaces.
Innovation Solution
An automated method and system using an AGV or AMR equipped with sensors and computing hardware to navigate and map the operating area, generate loading patterns, and correct load placement without the need for special equipment or infrastructure modifications, allowing for efficient and precise loading and unloading of pallets through rear access.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If specialized counterbalanced forklifts with tilt and side-shift mechanisms are used, then loading and unloading capability is improved, but device complexity and infrastructure requirements increase
Solution Approach 1:
The patent applies universality by enabling a standard forklift to perform both traditional side-loading and rear-loading operations through a programmable control system. The method allows the same vehicle to adapt to different loading scenarios (side entry and rear entry) without requiring specialized mechanical configurations, thus achieving multi-functionality with a single vehicle design.
Solution Approach 2:
The patent replaces complex mechanical systems (tilt and side-shift mechanisms) with a programmable control system that manages fork positioning through software algorithms. The control system processes sensor data and generates control signals to achieve precise load placement without requiring additional mechanical actuators, thereby substituting mechanical complexity with electronic control.
2Productivity
If loads are placed tightly next to each other to maximize space utilization, then productivity is improved, but measurement precision and detection difficulty increase
Solution Approach 1:
The patent implements feedback by continuously monitoring the positions of loads and the forklift using sensors, comparing actual positions with target positions, and adjusting the forklift's movement accordingly. The control system receives real-time data from sensors about load placement and uses this feedback to generate corrective control signals, ensuring precise positioning even when loads are placed tightly together with minimal clearance.
Solution Approach 2:
The patent replaces manual measurement and positioning methods with an automated sensor-based detection system. Optical sensors and other detection devices measure load positions and dimensions automatically, eliminating the need for physical measurement tools and human judgment, thereby achieving high measurement precision required for tight load placement.
3Extent of automation
If motor current or pressure sensors are used to detect load contact, then automation is improved, but reliability decreases due to stuck loads and false sensing
Solution Approach 1:
The patent merges multiple sensing methods (motor current sensing, pressure sensing, and optical sensing) into a unified control system. By combining these different sensing approaches, the system cross-validates detection signals and reduces false positives, thereby improving reliability while maintaining high automation. The control system integrates data from multiple sources to make more accurate determinations about load contact and placement status.
4Adaptability or versatility
If manual loading operations are performed, then adaptability is improved, but productivity and time efficiency worsen
Solution Approach 1:
The patent applies self-service by implementing an autonomous control system that performs loading operations without human intervention. The system automatically plans loading sequences, controls forklift movements, positions loads, and monitors completion status. This automation maintains the adaptability of manual operations while dramatically increasing productivity and speed.
Data Source
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AI summary
According to the present invention, a method for controlling an automatic guided vehicle (AGV) to transport at least two loads from a load picking-up area to an operating area in which the at least two loads are to be placed in corresponding loading areas is provided. This method can comprise the steps of picking-up a first load with the AGV in the load picking-up area, guiding the AGV with the first load by guiding means from the load picking-up area to the operating area, moving the AGV in the operating area to map virtual boundaries in the operating area within which the at least two loads are to be placed in the corresponding loading areas, generating a loading pattern for placing the at least two loads in the corresponding loading areas within the virtual boundaries in the operating area and generating travel trajectories which the AGV has to travel with each of the at least two loads to place the at least two loads in the corresponding loading areas, placing the first load in the corresponding loading area based on the generated loading pattern and the generated travel trajectory for the first load, mapping the operating area with the placed first load placed in the corresponding loading area and verifying whether the first load in the corresponding loading area corresponds to the loading pattern in such a manner that the at least one further load is able to be placed according to the loading pattern, and if the first load in the corresponding loading area does not correspond to the loading pattern in such a manner that the at least one further load is able to be placed according to the loading pattern, correcting the position and/or orientation of the first load in such a manner that the at least one further load is able to be placed according to the loading pattern.