Zoned Box Gripper Control for Mixed-SKU Container Picking
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Solution Overview
Problem
Current robotic systems fail to accurately pick and manipulate boxes of varying sizes and orientations from containers with walls due to misjudgment of size and position, often resulting in slipping or incorrect picking, as they struggle to distinguish physical edges from visual edges with advertising, logos, or textures.
Innovation Solution
A zoned gripper system with a control system that divides the gripper's grip area into zones based on minimum box size, uses a visual sensor to locate candidate boxes, determines a grasp pose that avoids container walls, and activates zones to lift the target box without overlapping neighboring boxes, ensuring sufficient suction force and avoiding container features during removal.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a conventional robotic system uses a single uniform gripper to pick boxes, then the system structure is simple, but the system fails to accurately distinguish physical edges from visual edges on boxes with advertising, logos, or textures, resulting in misjudgment of box size and position
Solution Approach 1:
The gripper is divided into multiple independently controllable zones with different suction forces. Each zone can be selectively activated based on the detected box size and position, allowing precise manipulation while maintaining overall system simplicity. The segmentation of the gripper into zones enables differential suction control without requiring complex mechanical structures.
Solution Approach 2:
The gripper transitions from a static, uniform suction configuration to a dynamic, selectively activatable zone-based system. The control system dynamically determines which zones to activate based on real-time box detection, enabling adaptive grasping forces that match the actual box characteristics rather than using a fixed gripper configuration.
2Reliability
If the robot activates all zones of the gripper to ensure sufficient suction force, then the grasping reliability is improved, but the robot may pick two or more boxes where it should have picked only one
Solution Approach 1:
Different zones of the gripper are assigned different suction force characteristics matched to local box characteristics. The control system selectively activates only the zones that correspond to the target box boundaries, applying appropriate suction force locally while leaving other zones inactive. This prevents accidental grasping of neighboring boxes while ensuring sufficient force on the target box.
3Adaptability or versatility
If the robot uses a large gripper to accommodate varying box sizes, then the adaptability to different box sizes is improved, but the gripper may overlap with neighboring boxes or container walls, causing collisions or incorrect picking
Solution Approach 1:
The large gripper is segmented into multiple independently controllable zones. The control system activates only the zones that align with the target box, effectively reducing the active gripping area to match the box size. This allows the physical gripper to be large enough to accommodate varying box sizes while preventing overlap with neighboring boxes through selective zone activation.
4Adaptability or versatility
If the robot relies on computer-vision-based systems to identify box edges, then the system can handle boxes with visual features, but the system cannot distinguish physical edges from visual edges, resulting in misjudgment
Solution Approach 1:
The zoned gripper acts as an intermediary between the visual detection system and the physical box manipulation. While the vision system provides candidate box locations, the zoned gripper's selective zone activation serves as a verification mechanism that refines the actual physical boundaries. The differential suction control provides tactile feedback that confirms true physical edges versus visual artifacts.
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 reliable and precise picking of individual boxes of varying sizes and orientations from mixed-SKU containers by accurately determining grasp poses and motion paths, reducing collisions and ensuring successful box removal while maintaining container structure integrity.
Implementation Method 1
The robot includes a gripper with a plurality of vacuum suction cups
Data Source
AI summary
A method of manipulating boxes includes receiving a minimum box size for a plurality of boxes varying in size located in a walled container. The method also includes dividing a grip area of a gripper into a plurality of zones. The method further includes locating a set of candidate boxes based on an image from a visual sensor. For each zone, the method additionally includes, determining an overlap of a respective zone with one or more neighboring boxes to the set of candidate boxes. The method also includes determining a grasp pose for a target candidate box that avoids one or more walls of the walled container. The method further includes executing the grasp pose to lift the target candidate box by the gripper where the gripper activates each zone of the plurality of zones that does not overlap a respective neighboring box to the target candidate box.