Vision-Guided Depalletizer Gripper for Dual Object Picking
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Solution Overview
Problem
Existing depalletizing systems struggle to efficiently pick up multiple objects of the same kind simultaneously due to variations in size and shape, leading to reduced loading speed on conveyor lines.
Innovation Solution
A depalletizing system utilizing a camera unit for image data acquisition, a controller for vision recognition, and a picking robot with a gripper and clamps to identify and pick up multiple adjacent objects of the same kind by adjusting gripper components based on object size and shape.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a robot with a gripper is used to pick up objects one at a time, then the system can handle irregularly sized and shaped objects, but the loading speed on the conveyor line is reduced
Solution Approach 1:
The gripper is divided into multiple gripper bodies (first, second, third, fourth) that can independently move and grasp different objects. Each gripper body can be controlled separately to pick up multiple objects simultaneously, resolving the contradiction between handling irregular objects and maintaining high loading speed
Solution Approach 2:
The gripper bodies are designed to move dynamically along the robot arm and can be positioned independently to adapt to different object sizes and shapes. This dynamic adjustment capability allows the system to maintain versatility while picking up multiple objects at once to improve loading speed
2Productivity
If multiple objects are picked up at a time to improve loading speed, then productivity increases, but the system complexity increases due to the need for vision recognition and coordinated control
Solution Approach 1:
A controller serves as an intermediary that coordinates between the vision recognition system and the multi-body gripper. The controller receives image data, identifies multiple objects, and generates coordinated control signals for the gripper bodies, simplifying the overall system architecture while enabling multiple object pickup
Solution Approach 2:
The system replaces manual mechanical picking with an automated vision-guided robotic system. The vision recognition system automatically identifies objects and their positions, eliminating the need for complex mechanical positioning mechanisms and reducing overall system complexity while improving productivity
3Adaptability or versatility
If the gripper is designed to accommodate multiple object sizes, then adaptability improves, but the gripper structure becomes more complex
Solution Approach 1:
The gripper is segmented into multiple independent gripper bodies that can be selectively activated based on object size and position. This segmentation allows the system to handle various object sizes using only the necessary gripper bodies, avoiding the need for a single complex adjustable mechanism
Solution Approach 2:
Each gripper body is designed with universal functionality to grasp different object types, and the combination of multiple gripper bodies provides even greater versatility. This multi-functionality approach achieves high adaptability while keeping individual gripper body structures relatively simple
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 enables faster object picking by identifying and grasping multiple objects at once, improving loading speed and efficiency on conveyor lines.
Implementation Method 1
a gripper connected to one end of the robot arm to suck the objects to be picked up with a pneumatic pressure
Data Source
AI summary
The present invention relates to a depalletizing system and a method for controlling the same. The depalletizing system, which picks up a plurality of objects to move the picked up objects to a predetermined position, includes: a camera unit for acquiring image data of tops of the plurality of objects; a controller for performing vision recognition for the acquired image data of tops of the plurality of objects to determine whether two neighboring objects among the plurality of objects are pickable at a time; and a picking robot for at a time picking up the two objects determined as pickable objects at a time to move the picked up objects to the predetermined position.