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Design Example01:23

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The innovation of touch-tone telephony revolutionized the telecommunications industry by replacing the traditional rotary dial with a dual-tone multi-frequency (DTMF) signaling system. This system uses a matrix-style keypad with buttons arranged in four rows and three columns, creating 12 distinct signals each assigned to a pair of frequencies. Each button press results in a simultaneous generation of two sinusoidal tones – one from a low-frequency group (697 to 941 Hz) and one from a...
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Language, whether spoken, signed, or written, consists of specific components: lexicon and grammar. The lexicon is the vocabulary of a language, comprising its words. Grammar is the set of rules used to convey meaning through the lexicon. For example, English grammar adds “-ed” to most verbs to indicate past tense. Words are formed by combining phonemes, which are the basic sound units of a language. Different languages have different sets of phonemes (e.g., “ah” vs.
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Related Experiment Video

Updated: May 6, 2026

A Structured Rehabilitation Protocol for Improved Multifunctional Prosthetic Control: A Case Study
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Large language model-driven natural language interaction control framework for single-operator bimanual

Haolin Fei1, Tao Xue2, Yiyang He1

  • 1School of Engineering, Lancaster University, Lancaster, United Kingdom.

Frontiers in Robotics and AI
|August 1, 2025
PubMed
Summary
This summary is machine-generated.

A new AI assistant, the bimanual teleoperation large language model assistant (BTLA), enables one operator to control two robotic arms using voice commands and teleoperation. BTLA significantly improves task success and reduces operator workload.

Keywords:
bimanual manipulationembodied AIhuman-robot collaborationlarge language model (LLM)teleoperation

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Area of Science:

  • Robotics
  • Human-Computer Interaction
  • Artificial Intelligence

Background:

  • Bimanual teleoperation presents significant cognitive and coordination challenges for single operators.
  • Distributing control to multiple operators can create decision-making ambiguities and reduce efficiency.

Purpose of the Study:

  • To introduce a novel framework, the bimanual teleoperation large language model assistant (BTLA), designed to enhance single-operator control of two robotic arms.
  • To augment operator capabilities by integrating AI for intuitive control and task execution.

Main Methods:

  • The BTLA framework utilizes the GPT-3.5-turbo model to interpret voice commands for controlling a secondary robotic arm.
  • Operators maintain direct teleoperation control of the primary arm while issuing voice commands for the assistive arm.
  • The system autonomously selects from six predefined manipulation skills, including mirroring, trajectory following, and object grasping.

Main Results:

  • BTLA demonstrated a 76.1% increase in task coverage and a 240.8% increase in success rate compared to solo teleoperation.
  • Compared to dyadic control, BTLA achieved a 19.4% gain in coverage and a 69.9% gain in success rate.
  • Operator mental workload was reduced by 38-52% (NASA-TLX), with 85% finding the voice interaction natural and effective.

Conclusions:

  • The BTLA framework offers a significant advancement in bimanual teleoperation by enhancing operator efficiency and reducing cognitive load.
  • AI-powered voice command integration provides a natural and effective method for complex robotic control tasks.
  • BTLA represents a promising approach for improving human-robot collaboration in various applications.