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相关概念视频

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

3.8K
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...
3.8K
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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相关实验视频

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大型语言模型的延迟感知基准测试用于ROS 2中的自然语言机器人导航.

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

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

Sensors (Basel, Switzerland)
|January 28, 2026
PubMed
概括
此摘要是机器生成的。

本研究介绍了使用大型语言模型 (LLM) 和机器人操作系统2 (ROS 2) 的自然语言机器人导航的新框架. 它对LLM和规划者进行了比较,揭示了响应速度和导航准确性之间的权衡.

关键词:
导航2 (Nav2) 是一个导航系统.ROS 2 2 的使用情况.人与机器人的互动大型语言模型.延迟的基准测试 延迟的基准测试地方规划师 地方规划师自然语言接口.机器人导航 机器人导航

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科学领域:

  • 机器人和人工智能 机器人和人工智能
  • 人与机器人的交互
  • 自然语言处理自然语言处理.

背景情况:

  • 移动机器人通常依赖于复杂的接口,阻碍非专家用户的访问.
  • 整合大型语言模型 (LLM) 提供了一条通往更直观,对话式机器人控制的道路.
  • 现有的系统缺乏对LLM驱动的导航进行全面的基准测试,特别是考虑到延迟.

研究的目的:

  • 开发和评估用于自然语言机器人导航的延迟感知基准测试框架.
  • 评估ROS 2导航2中的各种当代LLM和地方规划者的表现.
  • 提供对LLM大小,响应延迟和导航准确性之间的权衡的见解.

主要方法:

  • 开发了一个基准测试框架,将多个LLM与ROS 2 Nav2堆集成在一起.
  • 在 Gazebo Fortress 中使用模拟的 TurtleBot4 平台进行标准化的室内导航场景.
  • 与当地规划人员 (DWB,TEB,RPP) 进行基准LLM (例如GPT-4,Gemini 2.5,LLaMA-3.3),测量延迟,准确性,路径质量和成功率.

主要成果:

  • 在LLM大小,响应延迟和导航准确性之间展示了明确的权衡.
  • 较小的LLM提供了更快的响应,但空间推理较弱;较大的LLM显示出更好的导航意图,但延迟更高.
  • 在标准化任务中确定了不同LLM-planner组合的特定性能特征.

结论:

  • 拟议的框架允许在ROS 2内进行可重复的,多LLM,多计划器评估,用于自然语言机器人导航.
  • 这些发现支持为移动机器人开发直观,延迟效率高的对话接口.
  • 这项工作为更容易获得和更适应的机器人控制系统奠定了基础.