17.1人工智能x机器人:传感器、执行器和集成电路中的技术挑战和机遇

M. Fujita
{"title":"17.1人工智能x机器人:传感器、执行器和集成电路中的技术挑战和机遇","authors":"M. Fujita","doi":"10.1109/ISSCC.2019.8662358","DOIUrl":null,"url":null,"abstract":"In 1956 at the Dartmouth conference, the terminology of artificial intelligence (AI) was first used. In those days it was also called as symbolic AI (Symbolic-AI) [1]. For example, let us assume a block world problem in Fig 17.1.1 (right), where a block is represented as a symbol, “Block1”, and it can be operated by operators such as “PICKUP(Block1). In order to apply the operator “PICKUP” to the target object, “Block1”, the AI system has to check the pre-condition such as “CLEAR Block1”, which means there is no object on “Block1”. The Fig. 17.1.1 (right) shows an example of a task from State-A to State-B. The system has to search the possible operators and the pre-conditions so that State-B is achieved. There are many basic algorithms developed in Symbolic-AI era, which are often used today including the A*-search algorithm. Shakey is the representative example of intelligent robots based on Symbolic-AI. It was a wheel-based movable robot equipped with a TV-camera, Laser-Range-Finder, etc. It can move blocks in the real world using Symbolic-AI technologies. Its behavior control architecture is shown in Fig 17.1.1 (left). It has three steps, SENSE, PLAN, and ACT. Therefore, it is known as the SENSE-PLAN-ACT architecture. It is computationally intensive especially in the PLAN computation, therefore it is difficult if the environment is dynamically changing.","PeriodicalId":265551,"journal":{"name":"2019 IEEE International Solid- State Circuits Conference - (ISSCC)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"17.1 AI x Robotics: Technology Challenges and Opportunities in Sensors, Actuators, and Integrated Circuits\",\"authors\":\"M. Fujita\",\"doi\":\"10.1109/ISSCC.2019.8662358\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In 1956 at the Dartmouth conference, the terminology of artificial intelligence (AI) was first used. In those days it was also called as symbolic AI (Symbolic-AI) [1]. For example, let us assume a block world problem in Fig 17.1.1 (right), where a block is represented as a symbol, “Block1”, and it can be operated by operators such as “PICKUP(Block1). In order to apply the operator “PICKUP” to the target object, “Block1”, the AI system has to check the pre-condition such as “CLEAR Block1”, which means there is no object on “Block1”. The Fig. 17.1.1 (right) shows an example of a task from State-A to State-B. The system has to search the possible operators and the pre-conditions so that State-B is achieved. There are many basic algorithms developed in Symbolic-AI era, which are often used today including the A*-search algorithm. Shakey is the representative example of intelligent robots based on Symbolic-AI. It was a wheel-based movable robot equipped with a TV-camera, Laser-Range-Finder, etc. It can move blocks in the real world using Symbolic-AI technologies. Its behavior control architecture is shown in Fig 17.1.1 (left). It has three steps, SENSE, PLAN, and ACT. Therefore, it is known as the SENSE-PLAN-ACT architecture. It is computationally intensive especially in the PLAN computation, therefore it is difficult if the environment is dynamically changing.\",\"PeriodicalId\":265551,\"journal\":{\"name\":\"2019 IEEE International Solid- State Circuits Conference - (ISSCC)\",\"volume\":\"19 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-02-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 IEEE International Solid- State Circuits Conference - (ISSCC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISSCC.2019.8662358\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE International Solid- State Circuits Conference - (ISSCC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISSCC.2019.8662358","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

摘要

1956年,在达特茅斯会议上,首次使用了人工智能(AI)这个术语。在当时,它也被称为符号人工智能(symbolic -AI)[1]。例如,让我们假设图17.1.1(右)中的一个块世界问题,其中一个块被表示为符号“Block1”,并且它可以由诸如“拾取(Block1)”之类的运算符进行操作。为了将操作员“拾取”应用于目标物体“Block1”,人工智能系统必须检查“CLEAR Block1”等先决条件,这意味着“Block1”上没有物体。图17.1.1(右)显示了从状态a到状态b的任务示例。系统必须搜索可能的操作符和先决条件,以达到状态b。在Symbolic-AI时代开发了许多基本算法,包括A*搜索算法,这些算法现在经常使用。Shakey是基于Symbolic-AI的智能机器人的代表。它是一种轮式可移动机器人,配有电视摄像机、激光测距仪等。它可以使用Symbolic-AI技术在现实世界中移动方块。其行为控制架构如图17.1.1(左)所示。它有三个步骤:感知、计划和行动。因此,它被称为SENSE-PLAN-ACT架构。特别是在PLAN计算中,计算量非常大,因此在环境动态变化的情况下很难实现。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
17.1 AI x Robotics: Technology Challenges and Opportunities in Sensors, Actuators, and Integrated Circuits
In 1956 at the Dartmouth conference, the terminology of artificial intelligence (AI) was first used. In those days it was also called as symbolic AI (Symbolic-AI) [1]. For example, let us assume a block world problem in Fig 17.1.1 (right), where a block is represented as a symbol, “Block1”, and it can be operated by operators such as “PICKUP(Block1). In order to apply the operator “PICKUP” to the target object, “Block1”, the AI system has to check the pre-condition such as “CLEAR Block1”, which means there is no object on “Block1”. The Fig. 17.1.1 (right) shows an example of a task from State-A to State-B. The system has to search the possible operators and the pre-conditions so that State-B is achieved. There are many basic algorithms developed in Symbolic-AI era, which are often used today including the A*-search algorithm. Shakey is the representative example of intelligent robots based on Symbolic-AI. It was a wheel-based movable robot equipped with a TV-camera, Laser-Range-Finder, etc. It can move blocks in the real world using Symbolic-AI technologies. Its behavior control architecture is shown in Fig 17.1.1 (left). It has three steps, SENSE, PLAN, and ACT. Therefore, it is known as the SENSE-PLAN-ACT architecture. It is computationally intensive especially in the PLAN computation, therefore it is difficult if the environment is dynamically changing.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信