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Language01:16

Language

906
Language is a unique communication system that uses words and systematic rules to organize and transmit information. Unlike other forms of communication, which may involve postures, movements, odors, or vocalizations, language relies on symbols and grammar. This makes human communication distinct from that of other species, who also communicate but do not use language in the same way humans do.
Corballis and Suddendorf (2007) and Tomasello and Rakoczy (2003) highlight the role of language in...
906
Components of Language01:24

Components of Language

809
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.
809
Language Development01:22

Language Development

894
Children master language quickly and with relative ease, supported by both biological predisposition and reinforcement. B. F. Skinner (1957) proposed that language is learned through reinforcement, while Noam Chomsky (1965) argued that language acquisition mechanisms are biologically determined.
The critical period for language acquisition suggests that the ability to acquire language is at its peak early in life. As people age, this proficiency decreases. Language development begins very...
894
Language and Cognition01:27

Language and Cognition

763
Language serves as a bridge between ideas and communication, influencing how individuals perceive and interact with the world. Psychologists have long debated whether language shapes thought or vice versa. This discussion gained grip with Edward Sapir and Benjamin Lee Whorf in the 1940s, who proposed that language determines thought, a concept known as linguistic determinism. They suggested that the vocabulary and structure of a language influence how its speakers think and perceive reality.
763
Higher Mental Functions of the Brain: Language01:10

Higher Mental Functions of the Brain: Language

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Language is a system of communication that allows the expression of thoughts, ideas, and feelings. The brain processes language in both hemispheres.
Language formation and comprehension take place in the dominant hemisphere. The dominant hemisphere is responsible for understanding the meaning of spoken, written, or sign language, as well as the ability to communicate. For most people, the left hemisphere is the dominant one. The right hemisphere, then, gives tone and emotional context to the...
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Self-Awareness and Its Effects01:21

Self-Awareness and Its Effects

308
Self-awareness is a psychological state in which the individual becomes the focal point of their attention. This inward focus transforms the self into an object of contemplation and assessment, influencing how individuals perceive their actions and their alignment with personal and societal standards.Triggers and Contexts for Self-AwarenessSelf-awareness can be activated by external stimuli that make individuals visually or audibly aware of themselves, such as mirrors, cameras, or recordings.
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Related Experiment Video

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Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
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Latency-Aware Benchmarking of Large Language Models for Natural-Language Robot Navigation in ROS 2.

Murat Das1, Zawar Hussain1,2, Muhammad Nawaz1,3

  • 1Sydney Polytechnic Institute, Sydney, NSW 2000, Australia.

Sensors (Basel, Switzerland)
|January 28, 2026
PubMed
Summary
This summary is machine-generated.

This study introduces a new framework for natural language robot navigation using Large Language Models (LLMs) and Robot Operating System 2 (ROS 2). It benchmarks LLMs and planners, revealing trade-offs between response speed and navigation accuracy.

Keywords:
Navigation 2 (Nav2)ROS 2human–robot interactionlarge language modelslatency benchmarkinglocal plannersnatural-language interfacesrobot navigation

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Area of Science:

  • Robotics and Artificial Intelligence
  • Human-Robot Interaction
  • Natural Language Processing

Background:

  • Mobile robotics often relies on complex interfaces, hindering accessibility for non-expert users.
  • Integrating Large Language Models (LLMs) offers a path towards more intuitive, conversational robot control.
  • Existing systems lack comprehensive benchmarking for LLM-driven navigation, especially considering latency.

Purpose of the Study:

  • To develop and evaluate a latency-aware benchmarking framework for natural-language robot navigation.
  • To assess the performance of various contemporary LLMs and local planners within the ROS 2 Navigation 2 stack.
  • To provide insights into the trade-offs between LLM size, response latency, and navigation accuracy.

Main Methods:

  • Developed a benchmarking framework integrating multiple LLMs with the ROS 2 Nav2 stack.
  • Utilized a simulated TurtleBot4 platform in Gazebo Fortress for standardized indoor navigation scenarios.
  • Benchmarked LLMs (e.g., GPT-4, Gemini 2.5, LLaMA-3.3) with local planners (DWB, TEB, RPP), measuring latency, accuracy, path quality, and success rate.

Main Results:

  • Demonstrated clear trade-offs between LLM size, response latency, and navigation accuracy.
  • Smaller LLMs offered faster responses but weaker spatial reasoning; larger LLMs showed better navigation intent but higher latency.
  • Identified specific performance characteristics of different LLM-planner combinations in standardized tasks.

Conclusions:

  • The proposed framework enables reproducible, multi-LLM, multi-planner evaluations for natural-language robot navigation within ROS 2.
  • The findings support the development of intuitive, latency-efficient conversational interfaces for mobile robots.
  • This work lays the groundwork for more accessible and adaptable robot control systems.