Robotic Adaptive Production Online Program Modification
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Solution Overview
Problem
Existing robotic production systems lack the ability to adapt to changes in production conditions, leading to inefficiencies and potential errors, as they rely on pre-programmed instructions that do not account for real-time environmental variations or performance feedback.
Innovation Solution
Implementing methods and systems that allow for online modification of robot program instructions and control parameters based on sensor inputs during production, enabling adaptive adjustments to production tasks, such as modifying the robot's path to avoid collisions, optimizing process parameters, and learning from feature relationships to improve task efficiency and quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If pre-programmed instructions are used to control robots, then the control system is simple and reliable, but the system cannot adapt to changes in production conditions or environmental variations
Solution Approach 1:
The patent implements feedback mechanisms where sensor data from the production environment is continuously monitored and fed back to the control system. This enables the robot to detect changes in production conditions and automatically adjust its program instructions in real-time, resolving the contradiction between adaptability and control simplicity by introducing intelligent feedback loops rather than complex manual reprogramming
Solution Approach 2:
The control system transitions from static pre-programmed instructions to dynamic adaptive programming. The robot's control parameters and program instructions are modified online based on real-time sensor inputs, allowing the system to adapt to changing production conditions while maintaining a relatively simple hardware architecture through software-based adaptability
2Productivity
If pre-programmed instructions are used without modification, then the control system is simple to operate, but the production cycle time cannot be optimized in response to changing conditions
Solution Approach 1:
The robot control system performs self-optimization by automatically modifying its own program instructions based on sensor feedback and performance monitoring. The system autonomously adjusts control parameters to minimize cycle time and optimize production efficiency without requiring external intervention or complex manual reprogramming, thereby improving productivity while maintaining ease of operation
Solution Approach 2:
The system pre-establishes the capability for online program modification and parameter optimization during the initial setup phase. By preparing the adaptive control framework in advance, the system can quickly respond to changing production conditions and optimize cycle times in real-time without requiring complex operational interventions when changes are needed
3Reliability
If pre-programmed instructions are used, then the system is stable and reliable, but errors occur when production conditions change or new conditions arise
Solution Approach 1:
The patent employs feedback mechanisms where sensors continuously monitor production conditions and feed this information back to the control system. When environmental changes or new conditions are detected, the system automatically adjusts its program instructions to maintain reliable operation, resolving the contradiction between stability and adaptability through real-time feedback-driven adjustments
Solution Approach 2:
The control system dynamically changes operational parameters based on sensor inputs and detected production conditions. By modifying control parameters online rather than requiring complete reprogramming, the system maintains reliability through controlled, incremental adaptations to new conditions while preserving the core stable control architecture
Data Source
AI summary
A method for robotic adaptive production includes modifying program instructions online while performing production activities in response to detecting a change in the production environment. A robotic adaptive production method includes modifying program instructions online while performing production activities to minimize a production task cycle time or improve a production task quality. A robotic adaptive production method includes estimating a relationship between a control parameter and a sensor input; and modifying the control parameter online to achieve an updated parameter based on the estimating. A robotic adaptive production method includes receiving sensor input relating to robotic performance during the performance of production tasks and online optimizing a process parameter based on robotic performance during the performance of the production tasks. A robotic adaptive production method includes determining the position and/or orientation of a feature based on a learned position and/or orientation of another feature and on a geometric relationship.