Hand-Held Manipulation Task Suggestion Using Scene Analysis
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Solution Overview
Problem
Existing methods for training robots through imitation learning struggle with identifying appropriate tasks for a hand-held manipulation device, as users may find it difficult to select suitable tasks for collecting training data.
Innovation Solution
A hand-held manipulation device equipped with sensors and a camera captures images and video of tasks performed, which are analyzed by a vision language model (VLM) to suggest tasks based on the environment, allowing users to collect training data more effectively by performing suggested tasks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If users manually select tasks to collect training data, then the device complexity remains low, but the task selection difficulty increases and data collection efficiency decreases
Solution Approach 1:
The system automatically analyzes scene images and generates task suggestions without requiring user input or manual selection. The vision language model processes the scene image, identifies objects and relationships, and autonomously proposes appropriate manipulation tasks, allowing the system to serve itself rather than requiring active user participation in task selection.
Solution Approach 2:
A vision language model serves as an intermediary between the scene image and the task selection process. This intermediary component analyzes the image content, extracts relevant information about objects and their spatial relationships, and translates this into meaningful task suggestions, bridging the gap between raw visual data and actionable task ideas.
2Measurement precision
If the system provides task suggestions based on scene analysis, then the task identification accuracy improves, but the device complexity increases
Solution Approach 1:
The patent replaces manual visual analysis and mechanical decision-making with an automated vision language model. Instead of requiring users to visually inspect and select tasks, the system uses AI-based image processing and natural language generation to automatically identify appropriate tasks, substituting human cognitive processing with automated intelligent systems.
3Adaptability or versatility
If multiple tasks are suggested based on scene analysis, then the task diversity increases, but the time required for task selection increases
Solution Approach 1:
The system performs preliminary analysis of the scene image before task execution, automatically generating and presenting multiple task suggestions in advance. This preliminary action of analyzing the scene and pre-generating tasks eliminates the need for time-consuming real-time decision-making during task selection, as the heavy computational work is done beforehand.
Data Source
AI summary
A method includes receiving an image of a scene, receiving a request to identify tasks that may be performed by a user utilizing a hand-held manipulation device, based on the image of the scene, in response to receiving the request to identify the tasks that may be performed by the user utilizing the hand-held manipulation device, analyzing the image of the scene to determine one or more suggested tasks that may be performed by the user utilizing the hand-held manipulation device, outputting the one or more suggested tasks that may be performed by the user utilizing the hand-held manipulation device, and receiving training data in response to outputting the one or more suggested tasks that may be performed by the user utilizing the hand-held manipulation device.