Robot Skill Selection Control for Complex Manipulation Tasks
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Solution Overview
Problem
Existing robotic systems face challenges in selecting the correct sequence of skill primitives and their parameters under various scenarios, particularly for complex manipulation tasks, which are difficult and tedious to specify manually.
Innovation Solution
A method for controlling a robot device that includes providing a control model and a selection model, allowing for user input to train the selection model on the fly, using logistic regression for confidence-based decision-making, and employing a hierarchical approach with branch and edge selectors to determine skill sequences and parameters.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual specification of skill sequences and parameters is used, then the robot can perform tasks with human guidance, but the process becomes difficult and tedious for complex manipulation tasks
Solution Approach 1:
The selection model enables the robot to autonomously select skill sequences and parameters without continuous human intervention. The model learns from demonstrations and automatically makes decisions about which skills to execute and in what order, allowing the system to serve itself rather than requiring constant manual programming.
Solution Approach 2:
The patent replaces manual mechanical programming with an intelligent selection model that uses machine learning. Instead of manually specifying each skill sequence, the system uses a trained model that automatically determines the appropriate skill sequences based on learned patterns from demonstrations.
2Extent of automation
If a selection model is introduced to autonomously select functions, then automation increases, but the system requires training data and initial user input
Solution Approach 1:
The system performs preliminary training of the selection model using demonstration data before autonomous operation. This preliminary action prepares the model to make autonomous selections later, reducing the need for complex real-time decision-making infrastructure during actual task execution.
Solution Approach 2:
The system uses feedback from user corrections and task outcomes to continuously improve the selection model. When users provide corrections or when task outcomes are evaluated, this information feeds back into the model to refine its future selections, gradually improving automation without increasing operational complexity.
3Reliability
If the selection model is trained on user input during execution, then the model improves over time, but initial performance relies on user intervention
Solution Approach 1:
The selection model training continues continuously during system operation rather than being a separate offline process. As the robot executes tasks and receives user input or outcome feedback, the model learns in real-time, ensuring continuous improvement of selection accuracy while the system remains operational.
Solution Approach 2:
The system performs preliminary training with initial demonstration data before autonomous operation begins. This preliminary training establishes a baseline level of reliability, reducing the amount of user intervention needed during subsequent operations while the model continues to learn.
Data Source
AI summary
A method for controlling a robot device. The method includes providing a selection model and executing multiple instances of a task, including, in each execution, when a function of the robot device needs to be selected to perform the task instance, checking whether the selection model provides a selection of a function and, if yes, controlling the robot device to perform the function selected by the selection model and if no, receiving user input indicating a selection of a function, selecting a function according to the selection indicated by the user input, controlling the robot device to perform the function selected according to the selection indicated by the user input and training the selection model according to the selection indicated by the user input.