Robotic Container Packing for Stable Tight Incompressible Loads
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Solution Overview
Problem
Loading dissimilar objects into transport containers is challenging due to variations in size, weight, density, and rigidity, leading to instability and potential damage during transport, and existing robotic systems struggle to efficiently pack objects in a stable configuration within time constraints.
Innovation Solution
A robotic loading system that uses a vision system and computational models to optimize object placement, forming 'T' junctions and packing objects tightly against container walls to ensure stability, while also considering time and resource constraints, and employs a lightweight model for real-time decision-making.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If objects are packed tightly to optimize container usage, then container space utilization improves, but object stability deteriorates due to increased risk of collapse and damage
Solution Approach 1:
The system applies different packing densities to different regions of the container. Heavy, stable objects are placed at the bottom and against walls to provide structural support, while lighter objects are placed in upper regions. This localized quality differentiation allows tight packing in supported regions while maintaining stability in critical load-bearing areas.
Solution Approach 2:
The system performs preliminary stability analysis and simulation before finalizing the packing arrangement. Computational models evaluate potential packing configurations to predict stability outcomes, allowing the system to pre-arrange objects in a sequence and configuration that maximizes space utilization while ensuring stability is maintained throughout the loading process.
2Productivity
If robotic systems use complex algorithms to optimize object placement, then packing efficiency improves, but computation time increases beyond acceptable limits
Solution Approach 1:
The packing problem is segmented into multiple smaller sub-problems that can be solved independently and in parallel. The container space is divided into zones, and objects are categorized by properties such as weight, size, and stability requirements. This segmentation allows the system to process packing decisions for different object groups simultaneously, reducing overall computation time while maintaining packing efficiency.
Solution Approach 2:
The system uses simplified heuristic models and approximation algorithms instead of computationally expensive exact optimization methods. These lighter computational approaches provide sufficiently good packing solutions much faster, trading off some optimality for speed. The system can generate acceptable packing plans within time constraints, enabling real-time robotic packing operations.
3Quantity of substance
If dissimilar objects are loaded to maximize container capacity, then shipping cost efficiency improves, but load stability deteriorates due to variations in weight and rigidity
Solution Approach 1:
The system dynamically adjusts packing parameters such as object orientation, contact surfaces, and support structures based on the specific properties of each object. For dissimilar objects with varying weight and rigidity, the system modifies local packing density and support configurations to maintain overall load stability while maximizing container capacity utilization.
Data Source
AI summary
The present application discloses a method, system, and computer system for determining an arrangement of a set of objects for loading to a transport container. The method includes (i) receiving an indication of the set of objects to be loaded into the transport container for transport from a source location to a destination location, (ii) determining, based at least in part on object information corresponding to the set of objects, an arrangement of the set of objects loaded into the transport container according to a stability model, and (iii) providing the arrangement of the set of objects to a robotic system to implement in connection with loading the set of objects to the transport container.