Intel corporation (20240326242). SELF-RECONFIGURABLE ROBOT CONTROLLER simplified abstract

SELF-RECONFIGURABLE ROBOT CONTROLLER

Organization Name

intel corporation

Inventor(s)

Alejandro Ibarra Von Borstel of Manchaca TX (US)

Fernando Ambriz Meza of Manchaca TX (US)

Cornelius Buerkle of Karlsruhe (DE)

Jose Rodrigo Camacho Perez of Guadalajara (MX)

Hector Cordourier Maruri of Guadalajara (MX)

Paulo Lopez Meyer of Zapopan (MX)

Fabian Oboril of Karlsruhe (DE)

Julio Zamora Esquivel of West Sacramento CA (US)

Jose Miguel Hernandez Miramontes of Austin TX (US)

SELF-RECONFIGURABLE ROBOT CONTROLLER - A simplified explanation of the abstract

This abstract first appeared for US patent application 20240326242 titled 'SELF-RECONFIGURABLE ROBOT CONTROLLER

The abstract describes a self-reconfigurable controller for a robot that can communicate with peripheral devices, analyze functionalities, and generate a deep learning controller model to perform tasks.

• Input/output interfaces for communication with peripheral devices
• Processing circuitry to register peripheral devices and functionalities
• Conduct self-awareness check to correlate functionalities for tasks
• Generate a deep learning controller model based on correlations
• Control the robot to perform tasks efficiently

Potential Applications: - Industrial automation - Robotics research and development - Autonomous vehicles - Healthcare robotics - Smart home systems

Problems Solved: - Efficient task performance by robots - Seamless integration of peripheral devices - Adaptive and self-aware robotic controllers

Benefits: - Increased productivity and efficiency - Enhanced task accuracy - Flexibility in adapting to different tasks and environments

Commercial Applications: Title: "Self-Reconfigurable Robot Controller for Enhanced Task Performance" This technology can be used in various industries such as manufacturing, logistics, healthcare, and smart homes to improve automation processes and increase operational efficiency.

Questions about the technology: 1. How does the self-awareness check help in correlating functionalities for task performance? 2. What are the key advantages of using a deep learning controller model in robotics?

Original Abstract Submitted

a self-reconfigurable controller for a robot, including: input/output (i/o) interfaces to enable communication with i/o peripheral devices coupled to the robot; and processing circuitry that is operable to: register the i/o peripheral devices and associated functionalities; receive a command for the robot to perform a task; conduct a self-awareness check to correlate functionalities to perform the task with functionalities of the i/o peripheral devices; and generate, based on a net of deep learning (dl) models and a result of the correlation, a target deep learning controller (tdlc) model to control the robot to perform the task.