Robotic Cargo Unloading Using 3D Recognition and Adaptive Gripping
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
The unloading of parcel cargo from vehicles at logistics hubs is predominantly manual, leading to intense workloads and labor avoidance, necessitating the development of a robotic system for automating this process.
Innovation Solution
An automated cargo unloading machine equipped with robotic arm devices and conveyor belts, capable of recognizing cargo through edge and depth information, determining unloading order and mode, and employing suction, clamping, or sweeping mechanisms to unload cargo efficiently.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual unloading is used, then labor flexibility is maintained, but labor intensity and workload increase significantly
Solution Approach 1:
The patent replaces manual mechanical unloading operations with an automated robotic system that uses sensors, processors, and robotic arms to perform cargo extraction. The system substitutes human labor with automated machinery that can operate continuously without fatigue, thereby reducing labor intensity while increasing automation level.
Solution Approach 2:
The system enables self-service by allowing the robotic unloading system to autonomously perform the entire unloading process without continuous human intervention. The processor automatically generates unloading orders based on sensor data, and the robotic arm executes extraction tasks independently, making the system self-sufficient in performing its core function.
2Productivity
If automated robotic system is implemented, then unloading speed increases, but system complexity increases
Solution Approach 1:
The automated unloading system is divided into distinct functional modules: sensor units for cargo detection, processors for generating unloading orders, and robotic arms for execution. This segmentation allows each component to perform its specific function efficiently, increasing overall unloading speed while managing system complexity through modular design.
Solution Approach 2:
The robotic arm device is designed with multi-functionality to perform various unloading operations including gripping, lifting, and placing cargo. The system can adapt to different cargo types and unloading scenarios using the same basic robotic platform, thereby increasing productivity without proportionally increasing system complexity.
3Measurement precision
If cargo recognition based on edge and depth information is used, then recognition accuracy improves, but processing time increases
Solution Approach 1:
The system performs preliminary actions by capturing images and generating unloading orders in advance before the actual cargo extraction. The processor analyzes cargo positions and generates a sequence of unloading orders beforehand, allowing the robotic arm to execute pre-planned movements efficiently. This reduces real-time processing time while maintaining high recognition accuracy through advance analysis.
Solution Approach 2:
The system maintains continuous useful action by operating the robotic arm in a continuous sequence based on pre-generated unloading orders. Rather than pausing for real-time analysis during extraction, the system continuously executes pre-planned movements, thereby reducing overall processing time while the initial image analysis provides accurate cargo recognition.
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 effectively automates the unloading process, reducing manual labor intensity and improving operational efficiency in logistics centers by accurately identifying and handling various cargo types, including those with caution labels.
Implementation Method 1
a suction unit configured to suck the cargo positioned on the lower side among the cargo positioned in layers in the cargo box
Implementation Method 2
recognizing each of the loaded cargo in the loaded cargo image based on edge information and depth information of each object
Data Source
AI summary
An automated cargo unloading method and a computing device for performing the same. The method according to an embodiment is performed by an automated cargo unloading machine including one or more processors and a memory for storing one or more programs executed by the one or more processors, and the method includes obtaining a loaded cargo image photographed inside a cargo box in which cargo is loaded, recognizing each of the loaded cargo in the loaded cargo image based on edge information and depth information of each object, generating loaded cargo-related information including one or more of a position, a size, a type, and a loaded pattern of the cargo inside the cargo box of each of the recognized cargo, and determining one or more of an unloading order of the cargo inside the cargo box and an unloading mode of the cargo based on the loaded cargo-related information.