Vision-Guided Bin Picking for Adaptive Robotic Part Transfer
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Solution Overview
Problem
Current assembly processes rely on manual operations for moving parts from transport bins to manufacturing destinations, which are inefficient, cause ergonomic stress, and introduce delays due to repetitive motions and handling of heavy parts, leading to potential injuries.
Innovation Solution
A system and method utilizing a robot with an end effector and machine vision systems to automatically identify and move parts from a bin to a destination, including adaptive trajectory planning to navigate the robot and ensure accurate placement, reducing manual labor and improving efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual operations are used to move parts from bins to destinations, then flexibility and adaptability are maintained, but productivity decreases and ergonomic stress increases
Solution Approach 1:
The system enables self-service automation where the robot autonomously performs part picking and placement operations without human intervention. The robot navigates independently, identifies parts using vision systems, and executes transfer operations, allowing the system to serve itself rather than requiring manual labor for repetitive tasks.
Solution Approach 2:
The patent replaces the manual mechanical system of human workers with an automated robotic system. The robot's end effector, vision-guided navigation, and automated control systems substitute for human hands, eyes, and decision-making, eliminating ergonomic stress while maintaining operational capability.
2Loss of time
If manual part handling is performed, then adaptability to part variations is maintained, but loss of time increases due to repetitive motions
Solution Approach 1:
The system incorporates vision systems that continuously capture images of parts and the robot's environment, providing real-time feedback to the control system. This feedback loop enables the robot to identify part locations, orientations, and variations, then adjust its picking and placement actions accordingly, maintaining adaptability while operating at automated speeds.
Solution Approach 2:
The vision system performs preliminary identification and localization of parts before the robot executes pickup operations. By pre-processing visual information to determine part positions, orientations, and gripper approach paths, the system prepares all necessary data in advance, enabling rapid execution without sacrificing adaptability to part variations.
3Productivity
If automated robotic systems are implemented, then productivity increases, but device complexity increases
Solution Approach 1:
The robotic system is designed with multi-functionality to handle various part types, bin configurations, and destination locations using the same core platform. The end effector can adapt to different gripper types, the vision system can recognize diverse part geometries, and the navigation system can operate in different environments, reducing the need for multiple specialized systems.
Solution Approach 2:
The control system acts as an intermediary layer that manages the complexity between the physical robot components and the high-level task requirements. It coordinates vision data, navigation commands, gripper control, and safety monitoring through a unified software architecture, making the overall system easier to manage despite the complexity of individual components.
4Object-affected harmful factors
If heavy parts are handled manually, then cost is reduced compared to automation, but object-generated harmful factors increase due to worker fatigue and injury risk
Solution Approach 1:
The robot autonomously performs the hazardous task of lifting and moving heavy parts without human intervention. The system serves itself by using sensors to detect part weight and characteristics, then automatically adjusting gripper force and lift mechanics, eliminating the need for human workers to expose themselves to injury risks.
Solution Approach 2:
The patent replaces the human mechanical system with a robotic mechanical system capable of handling heavy loads. The robot's actuators, grippers, and support structures are engineered to bear and manipulate weights that would be unsafe for human workers, substituting the biological mechanical system with an engineered one that has no fatigue or injury risk.
Data Source
Figure 1
AI summary
A system and method for automatically moving one or more parts between a bin at a source location and a destination using a robot is provided. The system includes a first vision system to identify a part within the bin and to determine the pick location and pick orientation of the part. A second vision system determines the location and orientation of a destination inside or outside of the bin, which may or may not be in a fixed location. A controller plans the best path for the robot to follow in moving the part between the pick location and the destination. An end effector is attached to the robot for picking the part from the bin, holding the part as the robot moves it, and placing the part at the destination. The system may also check the part for quality by one or both of the vision systems.