Robotic Bin Picking Path Validation for Precise Grasping
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Solution Overview
Problem
Robotic bin picking is challenging due to the high accuracy and precision required, which current systems often cannot achieve, especially in environments with hazardous or heavy workpieces, making manual labor labor-intensive and risky.
Innovation Solution
A system and method that involve identifying candidate objects for robotic selection, determining feasible paths based on robotic constraints and environments, using kinematic models for collision avoidance, and validating grasping feasibility through graphical user interfaces for real-time control and path optimization, allowing for precise object manipulation and placement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If robotic bin picking is implemented to replace manual labor, then labor intensity and safety risks are reduced, but the required accuracy and precision exceed current system capabilities
Solution Approach 1:
The bin picking task is segmented into multiple independent stages: candidate object identification, path determination, feasibility validation, and execution. This segmentation allows each stage to be optimized independently, with validation ensuring that precision requirements are met before execution, thereby resolving the contradiction between automation and precision.
Solution Approach 2:
The system performs preliminary actions including identifying candidate objects, determining paths, and validating feasibility before actual picking execution. This preliminary validation ensures that all precision and constraint requirements are satisfied before the robot attempts the pick, enabling high-precision automation without exceeding system capabilities during execution.
2Manufacturing precision
If multiple validation and path determination steps are added to ensure precision, then picking accuracy improves, but system complexity and computation time increase
Solution Approach 1:
Complex validation and path determination operations are performed in advance before execution. The system pre-identifies candidate objects, pre-determines paths, and pre-validates feasibility, thereby ensuring high precision while keeping the actual execution phase simple and fast. This separates the computational complexity from the real-time operation.
Solution Approach 2:
The system dynamically adjusts the level of validation and path planning based on the specific task context. For simple picks, minimal validation is performed; for complex scenarios with constraints, more thorough validation is executed. This dynamic approach optimizes the balance between precision and complexity for each individual picking task.
Data Source
AI summary
A method and computing system comprising identifying one or more candidate objects for selection by a robot. A path to the one or more candidate objects may be determined based upon, at least in part, a robotic environment and at least one robotic constraint. A feasibility of grasping a first candidate object of the one or more candidate objects may be validated. If the feasibility is validated, the robot may be controlled to physically select the first candidate object. If the feasibility is not validated, at least one of a different grasping point of the first candidate object, a second path, or a second candidate object may be selected.