Wall-Based Robotic Packing for Overhang Placement in Containers
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Solution Overview
Problem
Robotic systems lack the sophistication to duplicate human sensitivity and adaptability for complex tasks, particularly in packing objects within containers, due to limitations in granularity of control and flexibility, as well as the inability to account for real-world deviations and uncertainties.
Innovation Solution
A robotic system with a wall-based packing mechanism that uses discretized models to derive packing plans, accounting for object and container geometries, and dynamically adjusts these plans to accommodate unexpected conditions such as deformed or misaligned container walls, by calculating separation distances and motion paths for efficient object placement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If traditional robotic packing methods are used, then automation is achieved, but flexibility and adaptability to real-world deviations are lost
Solution Approach 1:
The packing plan is made dynamic by allowing real-time adjustments based on sensor feedback. The system continuously monitors container wall positions and object placements, then dynamically recalculates packing plans to accommodate deviations such as misaligned walls or unexpected object positions, enabling the robotic system to adapt flexibly while maintaining automation.
Solution Approach 2:
A feedback mechanism is implemented where sensors detect actual container wall positions and object placements during packing operations. This feedback information is fed back to the control system, which then adjusts the packing plan accordingly, allowing the automated system to compensate for real-world deviations and maintain high adaptability.
2Manufacturing precision
If precise control is implemented for accurate packing, then manufacturing precision improves, but device complexity increases
Solution Approach 1:
The packing process is segmented into discrete steps: container detection, wall position measurement, packing plan generation, and execution. Each segment handles a specific aspect of the packing task, allowing precise control to be achieved through modular, manageable components rather than a monolithic complex system.
Solution Approach 2:
An intermediary computational layer is introduced that translates sensor data into adjusted packing plans. This intermediary processing step simplifies the overall control architecture by handling the complexity of real-time adjustments through algorithmic computation rather than requiring complex hardware control mechanisms.
3Productivity
If wall-based packing with overhanging objects is allowed, then packing efficiency increases, but stability control becomes more difficult
Solution Approach 1:
The system performs preliminary stability analysis before finalizing the packing plan. It calculates potential stability issues with overhanging objects and pre-adjusts the packing configuration to ensure stability, allowing efficient wall-based packing while preventing stability problems before they occur.
Solution Approach 2:
The system dynamically adjusts packing parameters such as object placement positions, orientations, and support structures based on real-time stability calculations. By changing these parameters adaptively, the system maintains both high packing efficiency through wall-based overhanging configurations and adequate stability through computed parameter optimizations.
Data Source
AI summary
A system and method for operating a robotic system to place objects into containers that have support walls is disclosed. The robotic system may derive a packing plan for stacking objects on top of each other. The robotic system may derive placement locations for one or more objects overhanging one or more support objects below. The derived placement locations may be based on utilizing one or more of the support walls to secure the placed object.