Robot Task Automation via Teleoperation Scripts and Action Primitives
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Solution Overview
Problem
Current technologies lack an efficient method to automate a wide range of tasks across various domains, requiring significant human intervention and expertise, and struggle to adapt robotic systems to perform complex tasks autonomously.
Innovation Solution
A framework that utilizes natural language instructions to generate scripts, which are then converted into ordered 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 fully autonomous execution of tasks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If robots are designed to perform specific tasks with high precision, then task execution reliability is improved, but adaptability to perform multiple different tasks deteriorates
Solution Approach 1:
The patent implements a universal robot system with a standardized body design that can perform multiple different tasks through interchangeable tools and modular components. The robot body serves as a universal platform that can be configured for various work objectives, resolving the contradiction between reliability for specific tasks and adaptability for multiple tasks.
Solution Approach 2:
The robot system is divided into separable modules including the robot body, tools, and end effectors that can be independently selected and combined. This segmentation allows the core robot body to maintain consistent reliable performance while different tool combinations enable adaptability to various tasks.
2Adaptability or versatility
If extensive training and programming are provided to robots, then their capability to perform complex tasks is improved, but the time and resources required for setup increase
Solution Approach 1:
The robot system incorporates self-learning and self-adjustment capabilities through sensors and feedback mechanisms that allow the robot to adapt to tasks with minimal external programming. The system can autonomously calibrate and optimize its performance, reducing the time and resources required for setup while maintaining high capability for complex tasks.
Solution Approach 2:
The patent implements pre-configured tool libraries and standardized interfaces that are prepared in advance, allowing rapid deployment of robot capabilities without extensive on-site programming or training when new tasks are introduced.
3Adaptability or versatility
If a robot system is designed with high adaptability to handle various tasks, then versatility is improved, but system complexity increases
Solution Approach 1:
The patent employs a universal robot body design with standardized mounting interfaces and control protocols that simplifies the system architecture. This universality allows multiple tools and end effectors to be integrated without increasing core system complexity, as they all interface with the same standardized platform.
Solution Approach 2:
The robot system uses nested modular components where tools and end effectors can be attached to and detached from the robot body in a hierarchical structure. This nesting approach allows versatility through tool combinations while maintaining simple control and management of the overall system.
4Ease of operation
If human operators directly control robots for task execution, then ease of operation is improved, but the extent of automation deteriorates
Solution Approach 1:
The robot system incorporates multiple sensors and feedback mechanisms that provide real-time information about task progress and environmental conditions. This feedback enables the robot to autonomously adjust its actions and make decisions, increasing automation while maintaining ease of operation through intuitive sensor-based control that mirrors human operational patterns.
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.