本体知识表示方法在机器人领域的应用研究综述

葛悦光; 张少林; 蔡莹皓; 鲁涛; 温大勇; 王海涛; 王硕

doi:10.11959/j.issn.2096-6652.202224

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本体知识表示方法在机器人领域的应用研究综述

专题：自主智能体灵巧精准操作学习 | 更新时间：2024-06-05

- 本体知识表示方法在机器人领域的应用研究综述
- A survey on applications of ontology knowledge representation in robotics
- 智能科学与技术学报 2022年4卷第2期页码：212-222
- 作者机构：
  
  1. 中国科学院自动化研究所复杂系统管理与控制国家重点实验室，北京 100190
  2. 中国科学院大学人工智能学院，北京 100049
  3. 中国科学院脑科学与智能技术卓越创新中心，上海 200031
- 作者简介：
  
  [ "葛悦光（1983− ），男，中国科学院自动化研究所复杂系统管理与控制国家重点实验室博士生，主要研究方向为知识型机器人" ]
  [ "张少林（1988− ），男，中国科学院自动化研究所复杂系统管理与控制国家重点实验室助理研究员，主要研究方向为智能机器人控制" ]
  [ "蔡莹皓（1983− ），女，中国科学院自动化研究所复杂系统管理与控制国家重点实验室副研究员，主要研究方向为机器人操作技能学习" ]
  [ "鲁涛（1979− ），男，博士，中国科学院自动化研究所复杂系统管理与控制国家重点实验室副研究员，主要研究方向为机器人模仿学习、强化学习" ]
  [ "温大勇（1975− ），男，中国科学院自动化研究所复杂系统管理与控制国家重点实验室高级工程师，主要研究方向为云计算平台、大型并行计算平台研发" ]
  [ "王海涛（1996− ），男，中国科学院自动化研究所复杂系统管理与控制国家重点实验室博士生，主要研究方向为知识推理、机器人任务规划" ]
  [ "王硕（1973− ），男，博士，中国科学院自动化研究所复杂系统管理与控制国家重点实验室研究员，中国科学院大学人工智能学院首席教授，国家重点研发计划“智能机器人”重点专项总体组专家，国际标准化组织ISO/TC 299专家，中国机电一体化技术应用协会常务理事。主要从事机器人学习、视触融合灵巧操作、仿生机器鱼、水下机器人−作业臂系统等研究。在国内外期刊和会议上发表学术论文120余篇，合著图书4本，获授权发明专利21项、软件著作权12项，主持制定机器人国家标准2项。主持我国科学技术部科技创新2030—“新一代人工智能”重大项目“自主智能体灵巧精准操作学习方法研究与验证”、国家863计划项目、国家自然科学基金联合基金重点项目和面上项目、支撑计划项目、国际合作项目、北京市科学技术委员会项目等多项项目。曾获得国家自然科学奖二等奖1项，北京市科学技术奖一等奖1项，省部级二等奖4项，中国自动化学会技术发明奖一等奖1项，中国自动化学会科普奖1项。中国科学院、中国自动化学会、中国人工智能学会优秀博士论文指导教师，曾获得中国科学院大学“领雁银奖·振翅奖”" ]
- 基金信息：
  
  国家重点研发计划资助项目;The National Key Research and Development Program of China(2019YFB1311901)
- DOI：10.11959/j.issn.2096-6652.202224
  中图分类号： TP242.6
- 网络出版日期：2022-06，
  
  纸质出版日期：2022-06-15
- 稿件说明：
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葛悦光, 张少林, 蔡莹皓, 等. 本体知识表示方法在机器人领域的应用研究综述[J]. 智能科学与技术学报, 2022,4(2):212-222.

Yueguang GE, Shaolin ZHANG, Yinghao CAI, et al. A survey on applications of ontology knowledge representation in robotics[J]. Chinese journal of intelligent science and technology, 2022, 4(2): 212-222.
葛悦光, 张少林, 蔡莹皓, 等. 本体知识表示方法在机器人领域的应用研究综述[J]. 智能科学与技术学报, 2022,4(2):212-222. DOI： 10.11959/j.issn.2096-6652.202224.

Yueguang GE, Shaolin ZHANG, Yinghao CAI, et al. A survey on applications of ontology knowledge representation in robotics[J]. Chinese journal of intelligent science and technology, 2022, 4(2): 212-222. DOI： 10.11959/j.issn.2096-6652.202224.

摘要

面临复杂非结构化的作业环境，知识表示方法在机器人自主作业中发挥着越来越重要的作用。知识表示关注于知识符号表征方式及如何通过推理程序自动实现知识处理。基于此，对基于本体表示与推理的机器人知识表示框架及最新应用进展进行了介绍。从确定性知识和不确定性知识两个方面，介绍了知识表示与推理的技术背景、实现方式和研究现状，并对机器人知识未来的研究方向进行了展望。

Abstract

The technology about knowledge representation plays an increasingly important role in the autonomous operation of robots facing the complex and unstructured working environment.Knowledge representation focuses on the model of knowledge symbols and how to realize knowledge processing through reasoning procedures automatically.The robot knowledge representation framework and the latest application progress based on ontology representation and reasoning were reviewed.The technical background

realization methods of knowledge representation and reasoning

and recent research progress in the robotics field were summarized from deterministic knowledge and uncertain knowledge.And the future research direction of knowledge-enabled robots was predicted.

关键词

Keywords

references

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