Multi-Function Robotic End Effector for Adaptive Part Handling
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Solution Overview
Problem
Existing robots require replacement or modification of end effectors for different tasks or parts, lacking flexibility in manufacturing processes.
Innovation Solution
A multi-function robot end effector with integrated magnets, vacuum subsystems, and mechanical gripping components, enhanced by AI software for part recognition and machine vision systems, allowing adaptive handling and re-orientation using re-orientation brackets.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a robot uses a specialized end effector for a specific task, then the robot can perform that task effectively, but the robot must be replaced or modified when a new task is required
Solution Approach 1:
The end effector integrates multiple gripping mechanisms (mechanical gripper, vacuum subsystem, magnetic component) into a single device that can perform multiple tasks. The controller selectively activates different subsystems based on part characteristics detected by the machine vision system, enabling one end effector to handle diverse parts and tasks without replacement or modification.
2Reliability
If the robot uses multiple separate end effectors for different tasks, then each task can be performed optimally, but the system complexity increases
Solution Approach 1:
The patent combines mechanical gripping components, vacuum subsystems, and magnetic components into a single integrated end effector assembly. This merging reduces the number of separate devices from multiple specialized end effectors to one multi-functional unit, thereby reducing system complexity while maintaining task performance effectiveness through selective activation of appropriate subsystems.
3Productivity
If the robot picks up parts in incorrect orientation, then handling speed may be maintained, but placement precision deteriorates
Solution Approach 1:
The machine vision system detects part orientation and characteristics before the robot picks up the part. The controller uses this advance information to select the appropriate gripping subsystem and adjust gripping parameters in advance, ensuring the part is grasped in the correct orientation from the start, thereby maintaining both handling speed and placement precision.
Solution Approach 2:
The machine vision system continuously monitors part orientation and position during handling. This feedback allows the controller to make real-time adjustments to the gripping force and robot motion to correct any orientation issues, ensuring precise placement while maintaining efficient handling speed through adaptive control.
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
Enables flexible and precise handling of parts with high accuracy (within 1-5 mm) and adaptability to different orientations without fixtureless systems.
Implementation Method 1
The end effector may comprise at least one magnet... magnets, physical support structures
Implementation Method 2
at least one vacuum subsystem... vacuum systems
Data Source
AI summary
System and methods for automatically selecting an end effector function for material handling are disclosed. A robot includes end effectors of different type. A controller receives image data from one or more machine vision components of a part at a workspace for handing by the robot. The controller analyzes the image data to determine characteristics of the part. Based, at least in part, on the analyzed image data, including the determined characteristics, the controller determines at least one of the end effectors to utilize for the part.