Object Sequencer for Container Loading Stability
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Solution Overview
Problem
The challenge lies in efficiently loading dissimilar objects into transport containers while ensuring stability, safety, and optimal space utilization, given the complexity of permutations and constraints such as weight distribution, robotic resource limitations, and time constraints in shipping and distribution environments.
Innovation Solution
A system and method that utilize a vision system, machine learning models, and physics engines to determine optimal loading plans by partitioning, sequencing, and arranging objects within transport containers, considering constraints like safety, time, and resource availability, using robotic arms and conveyors to implement these plans.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If objects are carefully selected and loaded to ensure stability and safety, then loading time and computational complexity increase, but loading safety and stability improve
Solution Approach 1:
The system performs preliminary computation of the loading plan before actual loading begins. The processor determines the optimal sequence of objects to be loaded by considering stability constraints, weight distribution, and space utilization in advance, allowing the robotic system to execute the pre-planned sequence without real-time decision delays
Solution Approach 2:
The system dynamically adjusts the loading sequence based on real-time feedback from sensors that monitor object properties, container state, and robotic system status. The loading plan can be modified during execution to accommodate unexpected conditions while maintaining safety constraints
2Volume of stationary object
If dissimilar objects are packed efficiently for storage and shipment, then space utilization improves, but complexity of handling and packing increases
Solution Approach 1:
The system applies different handling strategies and packing arrangements to different types of objects based on their specific properties. The processor analyzes object characteristics such as size, weight, shape, and fragility to determine optimal placement locations and orientations within the container, ensuring each object is handled according to its specific requirements
Solution Approach 2:
The system varies packing parameters such as object orientation, stacking height, and spacing based on the specific combination of objects being loaded. The processor adjusts these parameters dynamically to maximize space utilization while maintaining stability, rather than applying a fixed packing pattern to all object sets
3Productivity
If robotic systems are used to automate loading, then productivity increases, but adaptability to various object types and container configurations decreases
Solution Approach 1:
The robotic system is designed with universal capabilities to handle diverse object types and container configurations through programmable control. The processor can generate loading plans for various object geometries, weights, and material properties, as well as adapt to different container sizes, door configurations, and support structures, allowing a single robotic system to perform multiple loading tasks
Solution Approach 2:
The system incorporates sensors and vision systems that provide real-time feedback about object properties, container state, and robotic system position. This feedback loop allows the robotic system to automatically adapt to variations in object types and container configurations without human intervention, maintaining both productivity and versatility
Data Source
AI summary
The present application discloses a method, system, and computer system for sequencing a set of objects to be loaded into 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 and resources available to load the set of objects, a sequence according to which the set of objects are to be loaded into the transport container, and (iii) providing the sequence to a robotic system to implement in connection with loading the set of objects to the transport container.