平行机器人与平行无人系统:框架、结构、过程、平台及其应用

白天翔; 王帅; 沈震; 曹东璞; 郑南宁; 王飞跃

doi:10.16383/j.aas.2017.y000002

平行机器人与平行无人系统:框架、结构、过程、平台及其应用

doi: 10.16383/j.aas.2017.y000002 cstr: 32138.14.j.aas.2017.y000002

白天翔^1,2,3,,
王帅^1,3,,
沈震^1,2,4,,
曹东璞^2,5,,
郑南宁^6,,
王飞跃^1,7, ,

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 中国
2.
青岛智能产业技术研究院青岛 266000 中国
3.
中国科学院大学北京 100049 中国
4.
中国科学院云计算中心东莞 523808 中国
5.
英国克兰菲尔德大学驾驶员认知与自动驾驶实验室克兰菲尔德 MK430AL 英国
6.
西安交通大学人工智能与机器人研究所西安 710049 中国
7.
国防科技大学军事计算实验与平行系统技术中心长沙 410073 中国

详细信息

作者简介:
白天翔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研究生.主要研究方向为先进机器人控制, 机器人协调与机器人仿真.E-mail:baitianxiang2014@ia.ac.cn

王帅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研究生.主要研究方向为社会计算和平行管理.E-mail:wangshuai2015@ia.ac.cn

沈震中国科学院自动化研究所副研究员.主要研究方向为复杂系统, 智能制造.E-mail:zhen.shen@ia.ac.cn

曹东璞英国克兰菲尔德大学驾驶员认知与自动驾驶实验室主任.中科院自动化所客座研究员.主要研究方向为自动驾驶, 人车协同, 与平行驾驶.E-mail:d.cao@cranfield.ac.uk

郑南宁西安交通大学人工智能与机器人研究所教授.中国工程院院士.主要研究方向为模式识别与智能系统、机器视觉与图象处理.E-mail:nnzheng@mail.xjtu.edu.cn

通讯作者:
王飞跃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.国防科学技术大学军事计算实验与平行系统技术研究中心主任.主要研究方向为智能系统和复杂系统的建模、分析与控制.本文通信作者.E-mail:feiyue.wang@ia.ac.cn

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出版历程
- 收稿日期: 2016-12-28
- 录用日期: 2017-02-01
- 刊出日期: 2017-02-01

Parallel Robotics and Parallel Unmanned Systems: Framework, Structure, Process, Platform and Applications

BAI Tian-Xiang^{1,2,3
,},
WANG Shuai^{1,3
,},
SHEN Zhen^{1,2,4
,},
CAO Dong-Pu^{2,5
,},
ZHENG Nan-Ning^6
,,
WANG Fei-Yue^{1,7
, ,}

1.
The State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences (CAS), Beijing 100190, China
2.
Qingdao Academy of Intelligent Industries, Qingdao 266000, China
3.
University of Chinese Academy of Sciences, Beijing 100049, China
4.
Cloud Computing Center, CAS, Dongguan 523808, China
5.
Driver Cognition and Automated Driving Laboratory, Cranfleld University, Cranfleld MK43 0AL, UK
6.
Institute of Artificial Intelligence and Robotics (IAIR), Xi'an Jiaotong University, Xi'an 710049, China
7.
Research Center of Military Computational Experiments and Parallel Systems, National University of Defense Technology, Changsha 410073, China

More Information

Author Bio:
Ph. D. candidate at the State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences. His research interest covers advanced robotics control, robot coordination and robotics simulation

Ph. D. candidate at the State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences. His research interest covers social computing and parallel management

Associate professor at Institute of Automation, Chinese Academy of Sciences. His research interest covers complex systems and smart manufacturing

Director of Driver Cognition and Automated Driving Laboratory, Cranfield University, Visiting Professor at Institute of Automation, Chinese Academy of Sciences. His research interest covers automated driving, driver-automation collaboration and parallel driving

Professor at Institute of Artificial Intelligence and Robotics (IAIR), Xi'an Jiaotong University. Member of Chinese Academy of Engineering. His research interest covers pattern recognition and intelligent systems, computer vision and image processing

Corresponding author: WANG Fei-Yue Professor at the State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences. Director of the Research Center for Computational Experiments and Parallel Systems Technology, National University of Defense Technology. His research interest covers modeling, analysis, and control of intelligent systems and complex systems. Corresponding author of this paper

摘要

摘要: 本文将基于ACP（Artificial societies，computational experiments，parallel execution）的平行系统思想与机器人领域相结合，形成一种软硬件相结合的框架，为无人机、无人车、无人船在复杂环境中实验、学习与实际工作提供便捷、安全的平台，即平行无人系统.本文从平行机器人的基本概念出发，提出平行无人系统的基本框架，并介绍了各模块的基本功能与实现方法，探讨了其中的关键技术.然后本文围绕无人机、无人车、无人船三个方面展望了无人平行系统在实际中的应用和所面临的挑战，提出了平行无人系统的未来发展方向.
- 平行系统及理论 /
- 平行机器人 /
- 软件定义机器人 /
- 无人车 /
- 无人机 /
- 无人船
Abstract: In this paper, we propose a framework to incorporate robotics and software-defined surrogates using the ACP-based parallel systems theory. The framework offers a flexible, cost-effective and safe platform to develop and conduct experiments on UAVs, UGVs, USVs and AUVs, and links unmanned vehicles with cyber-physical-social systems (CPSS). This paper focuses on the structure of the proposed framework and each of the functional modules. Relevant tools, as well as further applications and challenges of the proposed system are also discussed.
- Parallel system and parallel theory /
- parallel robotics /
- software-defined robotics /
- UAV (unmanned aerial vehicle) /
- UGV (unmanned ground vehicle) /
- USV (unmanned surface vehicle)
注释:

1) 本文责任编委刘德荣

HTML全文

图 1 平行系统基本框架

Fig. 1 The basic framework of parallel system

下载: 全尺寸图片幻灯片

图 2 机器人软硬件结构

Fig. 2 Illustration of the hardware and software structures in robots

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图 3 平行机器人基本框架, 图片引用自[10]

Fig. 3 Basic framework of parallel robotics (the image is cited from [10])

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图 4 ACP平行系统流程图

Fig. 4 Flow chart of an ACP based parallel system

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图 5 平行无人系统计算实验框架

Fig. 5 Framework of computational experiments in parallel unmanned systems

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图 6 平行无人系统混合平行执行框架与原理

Fig. 6 Framework of the hybrid parallel execution process in parallel unmanned systems

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图 7 软件定义的机器人的软硬件框架

Fig. 7 Framework of software-defined robotics

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图 8 基于ROS/Gazebo的人工系统计算实验平台框架

Fig. 8 Illustration of a computational experiment platform in the artificial system based on ROS/Gazebo

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图 9 平行无人系统网络拓扑

Fig. 9 Network topology of a parallel unmanned system

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图 10 无人驾驶自主能力等级模型, 引用自[42]

Fig. 10 Illustration of the unmanned ground vehicles autonomy levels (UGVAL), the image is cited from [42]

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图 11 一种平行执行时序, 图片引用自[50]

Fig. 11 Illustration of a parallel execution sequence (the image is cited from [50])

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