Robotic Pack Adjustment for Irregular Container Conditions
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Robotic systems lack the sophistication to duplicate human sensitivity and adaptability for executing complex and intricate 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 dynamic pack adjustment mechanisms that generates discretized models of packing components, derives packing plans to stack objects with precise placement locations and separation distances, and dynamically adjusts plans to account for unexpected container conditions using sensors and real-time data to ensure efficient and flexible object placement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If traditional robotic systems are used for packing objects, then automation is achieved, but the system lacks flexibility and adaptability to account for real-world deviations and uncertainties
Solution Approach 1:
The robotic system dynamically adjusts packing plans in real-time based on sensor feedback and actual container conditions. The system transitions from static pre-programmed packing sequences to dynamic adaptive planning, allowing the robot to respond to deviations such as container irregularities, object position variations, and stacking uncertainties while maintaining automation.
2Manufacturing precision
If precise control is implemented for object placement, then packing precision is improved, but the system complexity increases
Solution Approach 1:
The system employs sensor feedback mechanisms to detect actual object positions, container conditions, and packing status in real-time. This feedback is fed back to the control system, which adjusts placement parameters and generates corrected motion plans, achieving precise control through closed-loop control rather than overly complex open-loop systems.
Solution Approach 2:
The robotic system dynamically modifies packing parameters such as placement positions, orientations, and sequencing based on real-time conditions. By changing parameters adaptively rather than using fixed complex control algorithms, the system achieves precision while managing complexity through parameter optimization.
3Adaptability or versatility
If dynamic adjustment mechanisms are added to account for real-world deviations, then adaptability is improved, but device complexity increases
Solution Approach 1:
The robotic system performs self-adjustment by autonomously detecting deviations through sensors and automatically generating corrected packing plans without requiring external intervention or complex manual reconfiguration. The system serves itself by adapting to real-world conditions, reducing the need for overly complex external control mechanisms.
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 detect an unexpected condition associated with a container during or before a real-time operation. Accordingly, the robotic system may dynamically adjust an existing packing plan based on detecting the unexpected condition.