Robot Teleoperation Scripts for Versatile Task Automation
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Solution Overview
Problem
Current technologies lack an efficient method to automate a wide range of tasks, particularly those requiring human-like dexterity and versatility, as existing robots require extensive programming and are limited in their ability to adapt to diverse work objectives.
Innovation Solution
A framework that uses natural language instructions to generate scripts, which are then converted into action commands from a library of reusable work primitives, allowing humanoid robots to autonomously perform tasks through a robot teleoperation system, enabling semi-autonomous or autonomous execution of tasks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional programming methods are used to control robots, then robots can perform specific tasks, but the complexity of programming increases and adaptability to diverse work objectives decreases
Solution Approach 1:
The system captures human demonstrations and creates digital copies of human actions through sensor data collection. The sensor system records human movements, forces, and contextual information, then stores this data as reusable action templates that can be replayed and adapted for similar tasks, eliminating the need for complex programming while maintaining task performance
Solution Approach 2:
The patent introduces an intermediary layer between human intent and robot execution. The sensor system and data processing algorithms act as intermediaries that translate natural human actions into robot-executable commands, allowing robots to perform tasks without direct complex programming by serving as a bridge between human demonstration and automated execution
2Adaptability or versatility
If extensive programming is used to enable robots to perform multiple tasks, then task versatility improves, but the time and resources required for programming increase
Solution Approach 1:
The system performs preliminary action by capturing and storing human demonstrations in advance. During the demonstration phase, sensors record human actions, environmental context, and task parameters, creating a library of pre-processed action templates that can be quickly retrieved and executed for similar future tasks, eliminating the need for time-consuming programming each time
Solution Approach 2:
The patent creates universal action templates through human demonstration that can be applied across multiple tasks. The sensor system captures fundamental human actions (grasping, moving, manipulating) that are task-agnostic and can be combined in different sequences to perform various work objectives, allowing one set of captured demonstrations to serve multiple functions
3Manufacturing precision
If robots are designed for special-purpose tasks, then task performance precision improves, but the ability to adapt to other tasks decreases
Solution Approach 1:
The system implements dynamics by allowing the robot system to adapt its behavior based on the specific task at hand. The sensor system continuously monitors environmental context and task requirements, then dynamically selects and adjusts the appropriate action templates from the captured demonstrations, enabling the same hardware to perform multiple tasks with precision by adapting its software behavior
Data Source
AI summary
Systems, methods, and computer program products for automating tasks are described. A multi-step framework enables a gradient towards task automation. An agent performs a task while sensors collect data. The data are used to generate a script that characterizes the discrete actions executed by the agent in the performance of the task. The script is used by a robot teleoperation system to control a robot to perform the task. The robot teleoperation system maps the script into an ordered set of action commands that the robot is operative to auto-complete to enable the robot to semi-autonomously perform the task. The ordered set of action commands is converted into an automation program that may be accessed by an autonomous robot and executed to cause the autonomous robot to autonomously perform the task. In training, simulated instances of the robot may perform simulated instances of the task in simulated environments.