Autonomous Truck Loader With Vision-Guided Robotic Manipulator
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Solution Overview
Problem
The existing methods for loading and unloading trucks are labor-intensive and costly, requiring human labor that is physically demanding and time-consuming, necessitating a more efficient and autonomous solution.
Innovation Solution
An autonomous device comprising a mobile body with a robot arm and a body conveyor system, equipped with a manipulator that can pick up and reconfigure rows of articles to match different orientations and locations within a truck, using vacuum cups and shelves to securely handle and position articles for efficient loading and unloading.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If human laborers are used to unload and load truck shipments, then flexibility in handling different cargo types is maintained, but physical difficulty and cost increase significantly
Solution Approach 1:
The patent replaces human labor with an autonomous robotic system that uses computer vision, machine learning, and automated mechanical components to perform loading and unloading tasks. The robot autonomously navigates the truck interior, identifies cargo locations, and executes loading/unloading operations without human intervention, thereby eliminating physical difficulty while maintaining operational flexibility.
Solution Approach 2:
The robotic system performs self-navigation and self-execution of loading/unloading tasks through autonomous decision-making. The machine learning algorithms enable the robot to independently plan its actions, avoid obstacles, and adapt to different cargo configurations without requiring human operators to manually control each operation.
2Adaptability or versatility
If human laborers manually handle separate articles, then adaptability to different article types is maintained, but time and labor costs increase
Solution Approach 1:
The system uses computer vision and machine learning to continuously monitor and adapt to different article types and cargo configurations. The robot receives visual feedback about the truck interior and cargo locations, processes this information through learning algorithms, and automatically adjusts its loading/unloading sequence and methodology to handle diverse articles efficiently.
Solution Approach 2:
The robotic system dynamically adapts its behavior based on real-time conditions. The machine learning component allows the robot to learn from different cargo scenarios and adjust its approach accordingly, enabling flexible handling of various article types while maintaining high operational speed through automated decision-making.
3Productivity
If a robotic system is implemented to reduce labor costs, then cost effectiveness improves, but device complexity increases
Solution Approach 1:
The robotic system is designed as a universal platform that can handle multiple types of cargo and perform various loading/unloading operations through a single integrated system. The machine learning algorithms and computer vision capabilities enable the same robot to adapt to different scenarios without requiring separate specialized equipment for each task type.
Solution Approach 2:
The system performs preliminary analysis of the truck interior and cargo locations using computer vision before executing loading/unloading operations. The machine learning algorithms process this preliminary information to plan the optimal sequence of actions, which simplifies the execution phase and reduces the overall complexity by preparing all necessary data in advance.
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 autonomous device significantly reduces the time and cost associated with truck loading and unloading by automating the process, enabling faster and more precise handling of articles across various orientations and locations within the truck.
Implementation Method 1
using vacuum and pneumatic systems to securely move and place rows of articles
Implementation Method 2
using vacuum and pneumatic systems to securely move and place rows of articles
Data Source
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AI summary
Embodiments include a robotic carton unloader (100) for unloading and loading articles, the robotic carton unloader (100) comprising: a mobile body (120) sized for driving in and out of a truck (10); a robotic arm (140) coupled to the mobile body (120) and configured to load and unload articles; a vision camera (127) configured to capture one or more images of one or more of a first location (16) and a second location (17) in the truck (10); a system control box (124) configured to determine an appropriate loading or unloading sequence for the robotic carton unloader (100) based on the captured one or more images of the first location (16) and the second location (17); and a manipulator (142) attached to a movable end of the robotic arm (140) to reconfigure to match an orientation of articles in the first location (16) and the second location (17) for unloading and loading articles based on the loading or unloading sequence.