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相关概念视频

Olfaction01:25

Olfaction

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The sense of smell is achieved through the activities of the olfactory system. It starts when an airborne odorant enters the nasal cavity and reaches olfactory epithelium (OE). The OE is protected by a thin layer of mucus, which also serves the purpose of dissolving more complex compounds into simpler chemical odorants. The size of the OE and the density of sensory neurons varies among species; in humans, the OE is only about 9-10 cm2.
The olfactory receptors are embedded in the cilia of the...
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Physiology of Smell and Olfactory Pathway01:20

Physiology of Smell and Olfactory Pathway

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Humans detect odors with the help of specialized cells located in the upper part of the nasal cavity, called olfactory receptor neurons (ORNs). ORNs possess hair-like structures called cilia, which are receptive to sensations from the inhaled air. When an odorant molecule binds to a specific receptor on the cell of the cilia, it leads to a series of events that ultimately cause the ORN to send electrical signals to the olfactory bulb in the brain through the olfactory nerves.
The olfactory...
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Olfactory Receptors: Location and Structure01:03

Olfactory Receptors: Location and Structure

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The process of olfaction, also known as the sense of smell, is a sophisticated chemical response system. The specialized sensory neurons that facilitate this process, known as olfactory receptor neurons, are situated in an upper segment of the nasal cavity, known as the olfactory epithelium. Olfactory sensory neurons are bipolar, with their dendrites extending from the epithelium's apex into the mucus that lines the nasal cavity. Airborne molecules, when inhaled, traverse the olfactory...
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Introduction to Special Senses01:26

Introduction to Special Senses

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Sensory receptors play an integral part in comprehending our external and internal environments. They receive diverse stimuli, converting them into the nervous system's electrochemical signals. This conversion occurs as the stimulus alters the sensory neuron's cell membrane potential, instigating the generation of an action potential. This action potential is subsequently transmitted to the central nervous system (CNS), which integrates with other sensory data or higher cognitive...
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Robotic Odor Source Localization via Vision and Olfaction Fusion Navigation Algorithm.

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通过多模式LLM集成视觉和嗅觉,用于机器人气味源定位.

Sunzid Hassan1, Lingxiao Wang2, Khan Raqib Mahmud1

  • 1Department of Computer Science, Louisiana Tech University, 201 Mayfield Ave, Ruston, LA 71272, USA.

Sensors (Basel, Switzerland)
|January 8, 2025
PubMed
概括
此摘要是机器生成的。

本研究介绍了一种用于移动机器人的新型气味源定位 (OSL) 算法,使用大型语言模型 (LLM) 集成视觉和嗅觉. 基于LLM的方法提高了复杂环境中的导航成功和速度,优于传统方法.

关键词:
大型语言模型 (LLM)多模式机器人技术多模式气味来源的定位和定位机器人操作系统 (ROS)

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科学领域:

  • 机器人技术 机器人技术 机器人技术
  • 人工智能的人工智能
  • 传感器融合式传感器

背景情况:

  • 气味源定位 (OSL) 对于未知环境中的自主代理来说至关重要.
  • 传统的OSL算法通常依赖于单个感官模式或复杂的监督学习.
  • 环境复杂性,如非单向空气流,可能会破坏仅嗅觉系统.

研究的目的:

  • 为移动机器人开发和验证一种新的OSL算法.
  • 使用大型语言模型 (LLM) 集成视觉和嗅觉传感器模式.
  • 在具有挑战性的现实世界条件下提高OSL性能.

主要方法:

  • 开发了一个基于LLM的OSL算法,包含"高层次推理"和"低层次行动"模块.
  • 集成的多模式传感器数据 (视觉和嗅觉) 进入LLM提示.
  • 在复杂的现实环境中,在移动机器人上实现和测试算法.

主要成果:

  • 拟议的基于LLM的算法与"只有嗅觉","只有视觉"和监督学习融合算法相比,表现出了更高的性能.
  • 在单向和非单向空气流场景中实现了更高的成功率和更短的平均搜索时间.
  • 有效地导航复杂的环境与障碍物和空气流中断.

结论:

  • 基于LLM的多模式传感器融合为气味源定位提供了强大而高效的方法.
  • 在LLMs的零射击推理能力消除了手动知识编码或定制监督模型的需要.
  • 这项技术在实际的搜索和导航任务中显著提升了自主代理的能力.