Robotic Pack Station Vision Control for Accurate Tote Picking
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Solution Overview
Problem
Robotic pack stations experience high failure rates due to incorrect item picking and inefficient operations, often causing the robotic end effector to pick the wrong items or totes, and can hinder smooth workflow in distribution centers and warehouses.
Innovation Solution
Implementing a computer-implemented method that utilizes artificial intelligence and machine learning models to guide robotic arms in picking and placing items, with human intervention for edge cases, and includes empty tote verification to prevent incorrect picking.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If traditional robotic pack stations are used, then automated item transfer is achieved, but high failure rates occur due to incorrect item picking
Solution Approach 1:
The vision system performs preliminary identification and verification of items before the robotic arm executes the picking action. The system captures images, identifies items and pick points, and verifies the correct item is selected before transfer, preventing incorrect picking.
Solution Approach 2:
The system uses vision systems to continuously monitor and verify item identification, pick point location, and successful item transfer. Feedback loops ensure that if an item is incorrectly identified or not properly transferred, the system can detect and correct the error.
2Extent of automation
If traditional robotic pack stations are used, then automated operation is achieved, but inefficient operations occur due to system interference
Solution Approach 1:
The robotic system performs self-verification of item identification and pick point location using integrated vision systems. The system automatically detects and corrects its own errors without external intervention, improving operational efficiency while maintaining automation.
Solution Approach 2:
The patent replaces mechanical verification methods with optical vision systems and AI-based item recognition. This substitution enables more efficient and accurate identification of items and pick points compared to traditional mechanical sensing methods.
3Speed
If empty tote verification is not implemented, then picking speed is maintained, but incorrect picking of empty totes occurs
Solution Approach 1:
The vision system performs preliminary verification to determine if a tote is empty before the robotic arm attempts to pick from it. This preliminary check prevents wasted picking attempts on empty totes while maintaining overall picking speed through efficient error prevention.
Data Source
AI summary
A vision system and control system for a robotic pack station is disclosed. Robotic pack stations typically include a work cell, which enables the transfer of items from a tote or a bin to a container. The work cell may include one or more of the following: a robotic arm, a vision system, a control system, a conveyor, and a pack platform. The vision system and control system of the present invention identify items and provide instructions to the robotic arm to pick and/or place items in a bin or a tote.