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Manned lunar exploration has once again become a hot pursuit among the international aerospace powers in the 21st century. The safety requirements for exploration missions are higher, and the missions are more complex and challenging. As a result, it has become a consensus to fully leverage and comprehensively utilize the respective advantages of humans and machines to carry out human-machine joint exploration. This paper reviews the current application status of automation and intelligence technologies in the field of lunar exploration. On this basis, the characteristics of future lunar human-machine joint exploration missions are analyzed. Four typical mission categories suitable for human-machine joint exploration are proposed, as well as five influencing factors that affect the effectiveness of human-machine cooperation. This paper also provides an in-depth analysis of the human factor risks and challenges in future human-machine joint exploration and proposes some suggestions for addressing human factor issues in future human-machine joint exploration on lunar surface from the perspectives of research program, ground facility construction, and relevant standard and system development.

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进入21世纪,载人月球探测再次成为世界航天大国的追逐热点。探测任务安全性要求更高、任务更加复杂而艰巨,充分发挥并综合利用人与机器各自优势开展人机联合探测已成为共识。文章首先分析了当前月球探测中自动化和智能化技术的应用现状,在此基础上对未来月面人机联合探测的任务特点进行分析,提出了适于人机联合探测的4种典型任务类别、影响人机协同效能发挥的5个方面的因素。面向未来的人机联合探测,文章深入分析了所面临的人因风险与挑战,并从研究布局、地面实施建设,以及标准和体系建设等方面提出了解决未来月面人机联合探测中人因问题的建议。

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陈善广,研究员,博士研究生导师。国际宇航科学院院士。人因工程全国重点实验室主任。曾任中国载人航天工程副总设计师。国家重点基础研究发展计划项目首席科学家。中国人类工效学学会常务理事兼复杂系统人因与工效学分会主任委员。主要从事人因工程方向研究。获国家科学技术进步奖特等奖1项、一等奖1项、二等奖1项,部省级科技成果一等奖7项、二等奖10项。出版学术专著8部,科普作品5部,译著3部。发表论文160多篇,授权发明专利20余件。电子信箱:。

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陈善广,研究员,博士研究生导师。国际宇航科学院院士。人因工程全国重点实验室主任。曾任中国载人航天工程副总设计师。国家重点基础研究发展计划项目首席科学家。中国人类工效学学会常务理事兼复杂系统人因与工效学分会主任委员。主要从事人因工程方向研究。获国家科学技术进步奖特等奖1项、一等奖1项、二等奖1项,部省级科技成果一等奖7项、二等奖10项。出版学术专著8部,科普作品5部,译著3部。发表论文160多篇,授权发明专利20余件。电子信箱:。

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陈善广,研究员,博士研究生导师。国际宇航科学院院士。人因工程全国重点实验室主任。曾任中国载人航天工程副总设计师。国家重点基础研究发展计划项目首席科学家。中国人类工效学学会常务理事兼复杂系统人因与工效学分会主任委员。主要从事人因工程方向研究。获国家科学技术进步奖特等奖1项、一等奖1项、二等奖1项,部省级科技成果一等奖7项、二等奖10项。出版学术专著8部,科普作品5部,译著3部。发表论文160多篇,授权发明专利20余件。电子信箱:。

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New York: ACM Press, 2006: 33-40., articleTitle=Common metrics for human-robot interaction, refAbstract=null), Reference(id=1242113393994302355, tenantId=1146029695717560320, journalId=1146032081894723586, articleId=1157393071936815166, doi=null, pmid=null, pmcid=null, year=2007, volume=4, issue=1, pageStart=null, pageEnd=null, url=null, language=null, rfNumber=[24], rfOrder=29, authorNames=Dautenhahn K, journalName=International Journal of Advanced Robotic Systems, refType=null, unstructuredReference=Dautenhahn K. Methodology & themes of human-robot interaction: A growing research field[J]. 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International Journal of Social Robotics, 2010, 2(4): 347-359., articleTitle=Review of human studies methods in HRI and recommendations, refAbstract=null), Reference(id=1242113394111742869, tenantId=1146029695717560320, journalId=1146032081894723586, articleId=1157393071936815166, doi=10.1177/0018720817695077, pmid=28324673, pmcid=null, year=2017, volume=59, issue=2, pageStart=172, pageEnd=188, url=null, language=null, rfNumber=[26], rfOrder=31, authorNames=Stowers K, Oglesby J, Sonesh S, journalName=Human Factors, refType=null, unstructuredReference=Stowers K, Oglesby J, Sonesh S, et al. A framework to guide the assessment of human-machine systems[J]. Human Factors, 2017, 59(2): 172-188., articleTitle=A framework to guide the assessment of human-machine systems, refAbstract=We have developed a framework for guiding measurement in human-machine systems.The assessment of safety and performance in human-machine systems often relies on direct measurement, such as tracking reaction time and accidents. However, safety and performance emerge from the combination of several variables. The assessment of precursors to safety and performance are thus an important part of predicting and improving outcomes in human-machine systems.As part of an in-depth literature analysis involving peer-reviewed, empirical articles, we located and classified variables important to human-machine systems, giving a snapshot of the state of science on human-machine system safety and performance. Using this information, we created a framework of safety and performance in human-machine systems.This framework details several inputs and processes that collectively influence safety and performance. Inputs are divided according to human, machine, and environmental inputs. Processes are divided into attitudes, behaviors, and cognitive variables. Each class of inputs influences the processes and, subsequently, outcomes that emerge in human-machine systems.This framework offers a useful starting point for understanding the current state of the science and measuring many of the complex variables relating to safety and performance in human-machine systems.This framework can be applied to the design, development, and implementation of automated machines in spaceflight, military, and health care settings. We present a hypothetical example in our write-up of how it can be used to aid in project success.), Reference(id=1242113394166268822, tenantId=1146029695717560320, journalId=1146032081894723586, articleId=1157393071936815166, doi=null, pmid=null, pmcid=null, year=2021, volume=16, issue=4, pageStart=605, pageEnd=621, url=null, language=null, rfNumber=[27], rfOrder=32, authorNames=许为, 葛列众, 高在峰, journalName=智能系统学报, refType=null, unstructuredReference=许为, 葛列众, 高在峰. 人-AI交互: 实现“以人为中心AI”理念的跨学科新领域[J]. 智能系统学报, 2021, 16(4): 605-621., articleTitle=人-AI交互: 实现“以人为中心AI”理念的跨学科新领域, refAbstract=null), Reference(id=1242113394220794775, tenantId=1146029695717560320, journalId=1146032081894723586, articleId=1157393071936815166, doi=null, pmid=null, pmcid=null, year=2021, volume=16, issue=4, pageStart=605, pageEnd=621, url=null, language=null, rfNumber=[27], rfOrder=33, authorNames=Xu W, Ge L Z, Gao Z F, journalName=CAAI Transactions on Intelligent Systems, refType=null, unstructuredReference=Xu W, Ge L Z, Gao Z F. Human-AI interaction: An emerging interdisciplinary domain for enabling human-centered AI[J]. CAAI Transactions on Intelligent Systems, 2021, 16(4): 605-621. 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journalRemark=《前瞻科技》是由中国科学技术协会主管,科技导报社主办、出版的科技智库型自然科学综合类学术期刊,于2022年创刊。办刊宗旨:紧扣国家科技创新需求,联合全国学会和科技智库机构,汇聚战略科学家、主流智库学者,通过提供战略性、前瞻性、权威性的思想观点和政策建议,为科技管理者和科研管理者供给高质量决策参考。, submitArticleUrl=null, websiteUrl=http://www.qianzhankeji.cn/CN/2097-0781/home.shtml, createdTime=1788948782498, updatedTime=1788948782498, createdBy=13041195026, updatedBy=13041195026, submissionGuidelinesUrl=http://www.qianzhankeji.cn/CN/column/column7.shtml, submissionAuthorUrl=https://qzkjauthor.cast.org.cn/webm/, submissionEditorUrl=https://qzkjeditor.cast.org.cn/webm/, submissionReviewUrl=https://qzkjauthor.cast.org.cn/webm/, submissionCeEditorUrl=https://qzkjeditor.cast.org.cn/webm/, submissionAeEditorUrl=https://qzkjeditor.cast.org.cn/webm/, option={"copyright":""}), JournalExt(id=1304509001270584270, language=EN, name=Science and Technology Foresight, nameHistory1=null, nameHistory2=null, managedBy=China Association for Science and Technology, sponsoredBy=Science and Technology Review Publishing House, 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月面人机联合探测的人因学问题
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陈善广 † , 王春慧
前瞻科技 | 综述与述评 2024,3(1): 22-33
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前瞻科技 | 综述与述评 2024, 3(1): 22-33
月面人机联合探测的人因学问题
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陈善广† , 王春慧
作者信息
  • 中国航天员科研训练中心人因工程全国重点实验室,北京 100094
  • 陈善广,研究员,博士研究生导师。国际宇航科学院院士。人因工程全国重点实验室主任。曾任中国载人航天工程副总设计师。国家重点基础研究发展计划项目首席科学家。中国人类工效学学会常务理事兼复杂系统人因与工效学分会主任委员。主要从事人因工程方向研究。获国家科学技术进步奖特等奖1项、一等奖1项、二等奖1项,部省级科技成果一等奖7项、二等奖10项。出版学术专著8部,科普作品5部,译著3部。发表论文160多篇,授权发明专利20余件。电子信箱:。

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†
Human Factors in Human-machine Joint Exploration on Lunar Surface
Shanguang CHEN† , Chunhui WANG
Affiliations
  • National Key Laboratory of Human Factors Engineering, China Astronaut Research and Training Center, Beijing 100094, China
出版时间: 2024-03-20 doi: 10.3981/j.issn.2097-0781.2024.01.002
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进入21世纪,载人月球探测再次成为世界航天大国的追逐热点。探测任务安全性要求更高、任务更加复杂而艰巨,充分发挥并综合利用人与机器各自优势开展人机联合探测已成为共识。文章首先分析了当前月球探测中自动化和智能化技术的应用现状,在此基础上对未来月面人机联合探测的任务特点进行分析,提出了适于人机联合探测的4种典型任务类别、影响人机协同效能发挥的5个方面的因素。面向未来的人机联合探测,文章深入分析了所面临的人因风险与挑战,并从研究布局、地面实施建设,以及标准和体系建设等方面提出了解决未来月面人机联合探测中人因问题的建议。

载人月球探测  /  人机联合探测  /  人机协作  /  人因学  /  人-系统整合

Manned lunar exploration has once again become a hot pursuit among the international aerospace powers in the 21st century. The safety requirements for exploration missions are higher, and the missions are more complex and challenging. As a result, it has become a consensus to fully leverage and comprehensively utilize the respective advantages of humans and machines to carry out human-machine joint exploration. This paper reviews the current application status of automation and intelligence technologies in the field of lunar exploration. On this basis, the characteristics of future lunar human-machine joint exploration missions are analyzed. Four typical mission categories suitable for human-machine joint exploration are proposed, as well as five influencing factors that affect the effectiveness of human-machine cooperation. This paper also provides an in-depth analysis of the human factor risks and challenges in future human-machine joint exploration and proposes some suggestions for addressing human factor issues in future human-machine joint exploration on lunar surface from the perspectives of research program, ground facility construction, and relevant standard and system development.

manned lunar exploration  /  human-machine joint exploration  /  human-machine cooperation  /  human factors  /  human-system integration
陈善广, 王春慧. 月面人机联合探测的人因学问题. 前瞻科技, 2024 , 3 (1) : 22 -33 . DOI: 10.3981/j.issn.2097-0781.2024.01.002
Shanguang CHEN, Chunhui WANG. Human Factors in Human-machine Joint Exploration on Lunar Surface[J]. Science and Technology Foresight, 2024 , 3 (1) : 22 -33 . DOI: 10.3981/j.issn.2097-0781.2024.01.002
自1969年美国“阿波罗计划”实现人类首次登月至今,尚无其他国家的航天员登上这颗离地球最近的天体,但无人月球探测活动却从未间断。月球是地球的天然卫星,无疑是人类飞出地球、开展深空探测的首选目标。进入21世纪,载人月球探测再次成为世界航天大国的追逐热点。2018年国际空间探索协调组发布了最新的全球探索路线图,采用了“近地轨道-地月空间-载人探火”的深空探测发展思路。2019年美国航空航天局(National Aeronautics and Space Administration, NASA)正式启动了“阿尔忒弥斯计划”,明确了无人月球探测、载人月球探索、开发利用月球和初期载人火星探索的发展路线图,并计划于2025年前后实现重返月球的目标。欧洲航天局(European Space Agency, ESA)提出国际月球村设想。中国也正式宣布启动载人登月计划,将建立月球科考站,实现长期月面驻留的任务目标[1-2]。
面对未来载人月球探测任务,人机联合探测受到高度关注,它将综合利用并发挥人与机器的各自优势来应对月球探测中更加复杂艰巨的工作。人是万物之灵,具有无可比拟的智慧,特别是对未知或非结构化情形的响应能力,也是目前任何机器系统无法替代的。但人类也存在明显的局限性,如必须有适宜生存环境、力量和速度有限、执行重复和单调任务时容易出错、容易受情绪影响等[3],也是人机系统中最不稳定的因素。在月面活动中,航天员要穿着登月服工作,着服状态下人的能力会降低,加上辐射、月尘、低重力等环境因素的影响,航天员安全性和操作工效都会面临较高风险。利用智能机器人代替人类可以完成大量烦琐、重复性高、危险或持续时间长的任务。在探测任务实施前由机器人进行月面作业现场的预先侦察、场地准备和居住舱建设等,为航天员的月面活动打前站。在航天员月面出舱活动期间,由机器人协助航天员作业,完成航天员无法独立完成的任务,如移动大的物体或者在月面进行大范围巡视勘察[4⇓-6],不仅涉及复杂月面探测任务中人机功能分配问题,还要面对如何实现航天员和机器人之间的高效协同,以最大限度地提高探测效能、任务成功率和科学回报率等更大的挑战。显然,要实现安全高效的月面人机联合探测,需要解决月面环境因素影响、人的能力特性变化、人机交互模式和人机协作等一系列人因问题。
目前,人类已经进行了多次月球探测。自苏联1959年实施月球探测以来,美国、俄罗斯、中国和印度等国家都开展了月球探测项目。美国是第一个成功将人类送上月球的国家。在1969—1972年,美国的“阿波罗计划”共实施了6次载人登月任务,将12名航天员送往月球表面。苏联于1959—1976年期间先后发射了约20颗月球探测器。中国月球探测的“嫦娥”计划于2007年开始,已经成功实施了“嫦娥一号”“嫦娥二号”“嫦娥三号”“嫦娥四号”和“嫦娥五号”任务,其中“嫦娥四号”实现了世界上首次在月球背面软着陆。印度于2008、2019和2023年分别发射了月球探测器“月船一号”“月船二号”和“月船三号”。这些月球探测任务旨在获取月面的地质和物理数据,研究月球的起源和演化,为未来的载人登月和可持续利用月面资源做准备。
在人类空间活动(包括月球探测活动)中,自动化和智能化技术的应用已经非常普遍,极大提升了人类的空间探索能力,主要包括3类:自动系统,用于监测和控制载人航天器和居住舱内的系统,如飞行控制系统、生命保障系统等;遥控机器人,通过直接命令操纵或通过其他临场感的交互方式,由航天员或地面飞行控制(简称飞控)人员控制的机器人,如国际空间站机械臂或火星探测器;协作机器人,在航天员附近与航天员协同作业,会受到与人类在工作中类似的功能约束,如可达性、可见性和情境感知等。
载人航天领域一直高度重视航天员与自动化系统交互中的人因研究,如针对航天器的人工控制,开展了大量的自动控制和手动控制人因研究,取得了航天器手控交会对接人因设计等一系列成果,自动化技术在降低航天员负荷、提高航天任务效率方面也发挥了重要作用。但是,以往飞行任务也发生了很多航天员-自动化系统整合不足引发的事故和风险,如“阿波罗10号”在飞行中出现航天员误操作问题、俄罗斯“进步234”号(Progress 234)飞船与“和平号”空间站(Mir Space Station)相撞等,这些也促使载人航天领域的人因工程专家不断梳理和深入分析自动化与航天员乘组之间整合面临的风险和挑战[5]。
美国和俄罗斯等在国际空间站开展大量人-机器人整合相关的人因研究,包括机械臂、漫游车、自由飞行机器人(如Astrobee)及人形机器人(如Robonaut 2)等,来评估人-机器人交互的方法[7-8]。
(1)星表探测机器人。美国、中国等都向月球、火星表面发射了探测机器人。由于距离、通信延迟等约束,地面人员实时交互控制基本不可能,一般采用开环控制模式。地面人员通过一系列指令进行控制。这些机器人相关的人因研究为未来月球探测中有监督的遥操作(Supervised Teleoperation)和自主控制(Autonomous Control)机器人提供了路径规划技术、操作者计划和指令的设计与验证,以及人机界面设计等诸多方面的人因设计经验。
(2)近地轨道的空间机械臂。航天飞机、国际空间站和中国空间站的大型舱外机械臂(图1(a)[9]),对舱外载荷和设备的安装维护、航天员出舱活动,以及大舱段和物品的舱外转运等起到了重要作用。对于中国空间站舱外机械臂的操控,舱内航天员一般通过位于核心舱内的机械臂操控台进行控制(图1(b)[9]),可以通过手柄对机械臂末端进行六自由度的控制,通过按键指令对机械臂单关节和末端进行控制,或通过路径规划引导机械臂自主运动,地面的飞控人员则通过指令序列对机械臂进行控制。人因学专家对于机械臂的操控方式、人机界面、天地/舱内外的人-机械臂协同模式等都进行了大量的研究,有效保障了机械臂的在轨安全运行。大量的空间飞行实践发现了一些人因设计不足:在复杂任务中,完全由航天员进行机械臂操控时工作负荷很高;舱外复杂的光照环境及有限的观察视角和画面,严重影响航天员情境意识;舱内外/天地间协同模式对机械臂运行效率影响很大等。在未来的月球探测任务中,环境条件相比空间站有很大不同,对机械臂自主运行及人机协同要求更高,需要更加关注人因问题的解决。
(3)先进机器人在轨验证。美国、俄罗斯和日本等都借助空间站开展了在轨的验证,如2011年2月美国将一个人形机器人Robonaut 2送入国际空间站。它由三自由度的头部、一自由度躯干、2个七自由度手臂和2个十二自由度的手组成(图2[5])。R2“类人”灵巧手,提供了与航天员相同的使用工具、把手和界面的能力,被用于协助航天员完成维修和维护任务。地面控制者和国际空间站乘组可以通过定制的Robonaut 2 GUI(Graphical User Interface,图形用户界面)和头戴式VR(Virtual Reality,虚拟现实)系统远程操作Robonaut 2。近年来,美国麻省理工学院、日本宇航探索局、德国航空航天中心和NASA相继研发出SPHERES、Int-Ball、CIMON(Crew Interactive Mobile Companion)和Astrobee(图3[10])等多型舱内飞行机器人,并开展了一系列人因工程和人机交互等关键技术研究和在轨试验[11-12]。
(4)面向未来星球探测的人-机器人协同作业的地面模拟试验。NASA在地面构建了各种空间模拟试验环境和机器人试验平台,研究人-机器人交互的复杂性,如不同类型的机器人系统、控制模式(手动控制、监督控制等)和运行概念(同一空间位置与近距离组队,一对多与多对一,机器人和航天员相对位置等)。对于在星球表面与航天员协同作业的机器人研发,还处于地面研究和实验阶段。NASA的ARSD(Automation Robotics Simulation Division)项目研究小组采用Boudreaux、Thibodeaux和SCOUT(Science, Crew, Operations, and Utility Testbed)等行星表面探测的机器人试验测试平台(图4[8]),开展野外试验场人-机器人协作中的人因问题研究[13]。
Boudreaux和Thibodeaux是电池驱动的四轮机器人,能够帮助航天员建造基地及探索周围环境,配有摄像机、激光器、GPS装置和角度姿态动态测量装置等传感器,还安装有七自由度机械臂和三指机械手。SCOUT可携带两名着舱外服的模拟航天员,提供手动驾驶、遥控驾驶和自主驾驶等多种操控模式。这些地面模式试验在机器人定向知识、任务知识、与人的身体互动、与人的言语交互方面都获得了很多发现。例如,机器人跟随航天员一起在月面移动,机器人的移动、避障等动作都较慢,而且适应性和可靠性有限,协作效率不高[8]。
人类要在月球上生活和工作,需要在月面建造居住舱和其他月面设施,并对其进行管理和维护。航天员在月面开展舱外作业需要着登月服,而着服状态下航天员的可视性、灵活性、力量及作业时间都受到约束,需要自动化智能化机器协同支持,人机联合探测将是未来载人月球探测的主要模式和技术形态。NASA针对未来深空探测中人与自动化/机器人整合技术进行了全面的分析评估,提出了9方面需要重点关注和发展的技术。① 人的意图理解,包括机器人对人的意图的解释和理解、改善人向机器人的沟通等。② 自主/机器人系统与航天员的沟通,向航天员更好地提供信息,涉及各种以直观、自然的方式向人有效提供信息的各种技术,包括多模态传感、可解释性和透明度等。③ 确保人身安全,研究如何在近距离共享环境中实现人和机器人的安全操作。④ 持续监视人的绩效,研究航天飞行需要关注的人-系统的效能指标和极限,以及测量这些指标的方法和技术的验证,理解自适应自动化对人员效能的影响,识别可调整和自适应自动化带来的人员效能差异等。⑤ 人机团队效能优化和功能分配,通过不同的途径理解人与机器人的团队协作及其鲁棒性,确定人机功能分配方案等,聚焦社会和团队工作要素如何支持人机协作。⑥ 复杂机器人系统的指挥/控制,关注多个不同种类的具有不同自主水平的机器人主体的指挥和控制、柔性的功能分配、支持人类使用自主系统做出时间紧迫决策的新方法等。⑦ 增强人-机器人系统的情境意识,聚焦维持与提高人在与自主/机器人系统进行交互时的情境意识的技术、人-自主系统监督模型等。⑧ 改善人-机器人系统和任务的训练。⑨ 建立对自动化/机器人系统的适当信任,研究相关的方法、影响因素和人-机器人团队的共享控制机制等[14]。
因此,为确保未来月面人机联合探测任务的顺利推进,分析未来载人月球探测的任务特点和影响人机协同效能发挥影响因素,规划布局月面人机联合探测人因研究迫在眉睫。
人机联合探测指的是航天员与具有自动化/智能化的系统或机器人联合完成某个特定的任务。在这个过程中,航天员必须与机器系统进行有效的交互与协同作业。不同的任务场景和任务要求,对人机联合探测的需求不同,对系统的自动化、智能化和自主能力的要求也不同,这些都会影响人机联合作业的模式。针对未来的载人月球探测,航天大国都给出了各自的运行概念设想,并对可能涉及的人机联合探测任务进行了分析[1,15-16]。
在载人月球探测任务中,航天员或者地面飞控人员需要对载人飞船、着陆器和月球车等各类航天器进行导航、控制和监视等操作。这类任务包括航天器从月球/地球表面的发射上升、进入/下降及着陆等;两个航天器之间的交会对接/分离;在月球表面进行的航天器驾驶和导航等。在不同的任务场景、航天器不同自动化和智能化水平下,航天员和航天器之间的职责和角色可能会有较大差异。航天器的自主水平包括完全自主、半自主和全人工控制,而航天员对航天器的操控包括直接操控和遥操作、路径规划、状态监视等。根据任务特点,充分利用两者的柔性,形成良好的分工,才能确保人机系统的综合效能。
航天员可以与自动化、智能化系统协作,共同完成对航天器的运行状态管理任务,所管理的航天器包括载人飞船、着陆器、月球车(加压或不加压)和月球基地等。由于航天器的自动化程度一般很高,异常状态下的故障检测、隔离和恢复是人机协作的核心任务。与空间站的近地轨道飞行任务相比,月面人机联合探测任务需要管理的系统种类更加多样,同时由于距离、时间延迟等约束,当航天器和设备(如电源、环境控制与生命保障等)出现异常时,航天员难以依靠地面的支持,必须与自动化/智能化系统进行交互,协同开展航天器数据和信息采集、分析决策和处置,完成故障检测、故障隔离和故障恢复等任务。
未来的载人月球探测任务将有大量的机器人参与其中,如地形探测机器人、月球基地建造机器人、月面科学探测机器人、航天员作业助手机器人等。这些机器人和航天员及地面飞控团队协作,在探测任务的各个阶段发挥重要作用。典型的协作任务包括与航天员协同进行建造组装,如大型机械臂支持航天员完成大舱段/物品的抓取/提升/停靠/安放等;月面科考活动支持,如利用航天员操控挖掘机器人实现土壤、岩石等的大量挖掘/转移,利用地形探测机器人进行月面地形的侦察/测绘等;机器人还可以辅助航天员执行出舱活动及舱内站务管理(如摄像、维修支持)等。这些机器人类型多样,功能、复杂程度、智能化和自主水平各不相同,作业场景多样(舱内、舱外和月面等),航天员与机器人的协同作业方式也不同,既有与机器人主体的直接连续的交互(如遥操作),也有采用固有的、不太频繁的监督控制模式等。
对于月球基地的建设/维护、长期驻月(包括载人和不载人状态交替)、月面极地科考等高复杂度任务,其规划既要考虑载人登月前预先部署的航天器、设备的数量和性能(如电力)等对月面探测载荷的支持能力等战略层面的因素,也要考虑乘组每日的工作安排、训练周期和程序等战术层面的因素。因此,任务规划和运行支持具有很大的挑战性。地月之间的距离和通信约束,要求长期驻留的航天员具有更高的自主开展任务规划和运行管理的能力。智能化系统能对此提供极大的支持,包括飞行前月球基地设备的预先部署规划、航天员日常工作安排、复杂操作任务作业流程的智能支持和物资信息的智能管理等。
要充分发挥航天员、自动化和智能化系统各自的优势,实现安全高效的人机联合探测,必须在设计人-自动化和智能化系统交互时,对影响人-系统整合的各方面因素进行深入分析,确保人-系统整体效能最优。高效的人机协同是人机联合探测的关键,需着重考虑以下几个方面的因素。
月面人机联合探测需要特别关注月面特因环境带来的约束,包括地球重力/空间微重力/月面低重力等不同重力环境的转换、月球表面非结构化的地形、月面特殊的光照环境(特别是月球极地位置存在一些永久阴影区等极端的光照条件)、通信的可靠性和延迟(特别是对月球极地的探索,将带来更长的通信延迟和更强的带宽限制)等。这些特殊因素会对人机联合探测任务带来极大的影响,必须在人机系统界面、人机交互和协同模式设计中予以充分考虑。
航天员能力特性及其在作业过程中的状态变化会影响人机协同作业的整体效能。月面人机联合探测对航天员能力特性的考虑,主要包括两方面。一是空间和月面特因环境对航天员能力特性影响,包括辐射、月尘、低重力和远距隔离等因素对航天员生理心理的影响,特别是航天员着登月服后运动、操作力量和感知觉等能力特性的变化。这些将构成人因设计所应依据的航天员能力基线。二是在任务执行过程中,航天员能力和状态的动态变化。自动化和智能化程度较高的任务或系统,在执行日常/常规任务时自主性很强,航天员介入少、负荷低,但在异常或紧急状态下需要航天员介入时,航天员需要对系统状态有较高的了解程度和情境意识水平。航天员的训练水平、认知决策、工作负荷和疲劳程度等对人机协同效率和安全性影响较大。人因设计时需重点关注动态人机功能分配、航天员能力监测等方面,以合理发挥航天员作用[14,17]。
月面人机联合探测面临复杂环境与任务的双重挑战[18],与航天员协作的机器人应具备相关的智能,至少包括4方面:双向交流/交互、安全评判、自我维护和自我监控。机器人还需具有较强的独立自主性,能够基于地形和任务的知识、人类需求相关的知识进行推理,理解人类意图,从而及时对人提供辅助,或在没有外部监控或控制的情况下独立完成任务。航天员在月面的能力会受到各种约束,其时间非常有限和宝贵。智能机器人辅助可提升航天员的作业效能。人-机器人交互面临操作鲁棒性和机器人处理任务层级目标的能力等主要挑战[19⇓-21]。机器人越智能,其能胜任的任务就越多,但也变得越复杂,必须综合权衡机器人系统智能化与可靠性、资源代价等之间的关系,因为越复杂的机器人,其可靠性、协同效率可能降低,因而会影响人机协同的效果和人-系统的安全性。
在未来的月面人机联合探测中,航天员将与载人飞船、月球基地的月面居住舱系统和物资舱系统、载人月球车(包括加压和不加压)、月面着陆器、大型机械臂和移动探测机器人等协同工作。机器系统的种类繁多,协同交互方式多样,不合理的协同模式会给航天员带来较大负荷,降低工作效能。面向月面人机协同模式的人因设计需满足直接、手动、共享和监督控制等多种模式,支持不同时间或空间的单个/多个航天员对多个机器人的操作控制,适应通信约束下的时间延迟等要求,才能保证人机协同任务的安全性、可靠性和效率。航天员和自动系统各自的优势和不足及任务的复杂度均会影响协同任务的分配和控制权的切换条件,因此应纳入人机协同模式人因设计的考虑。
人与机器人构成一个耦合系统整体。根据任务特点、人和机器人各自的优势进行合理任务分配和团队结构设计,有助于提高人机协同的效率。月面人机联合探测任务复杂、月面环境特殊及人的能力特性下降等方面不同程度地影响了人-机器人协同效能。与航天员协同的还有地面飞控团队,其动态实时支持能力相比近地轨道也明显下降。因此,人-机器人团队构成、人机交互界面设计和团队的协同作业模式是团队协作需重点关注的人因问题。团队构成需考虑机器人的数量、功能、人机功能分配、极端环境及机器人可靠性/安全性/维修性等设计约束,否则影响人-机器人协同作业效能。人和机器人的交互要保证良好的互理解性。若不同机器人的人机界面、交互模式等设计未兼顾一致性和独特性,未统筹易用性、易学性及防误等设计,尤其是未充分考虑航天员着舱外服后的人机交互方式(如声音或手势等)适用性,将会对人-机器人协同带来巨大的安全隐患,降低作业效能。团队的协同作业模式主要是确保航天员近身空间的协作机器人安全、高效。辅助机器人将以与航天员活动相匹配的速度或步骤来执行任务。机器人需具备较好的鲁棒性和可靠性。
未来自动化和智能化水平的提升,会对月面人机联合探测提供很多支持,但也要深刻认识到,不良的人机协同和合作关系可能导致事故。例如,“进步234”号与“和平号”碰撞,就是由人机交互设计问题引发的。NASA在2013年对人和自动化/机器人整合设计问题引发的风险进行了分析,在对大量案例进行分析的基础上,指出当人-机器人整合较差时,易引发航天员与安全相关的关键失误。NASA在2021年发布的Risk of Inadequate Human-System Integration Architecture报告中[5],也系统分析了与人和自动化/智能化系统整合不足引发的风险和问题。人-系统整合设计不当,其产生后果的原因可能是直接的(如航天员一个意外操作直接引发),也可能是长期和间接的(如航天员工作负荷过大引发),并且可能是由多种因素相互作用引发。
将功能或任务以不同方式分配给特定主体(人、自动化或机器人),会导致不同的绩效水平。目前针对人和自动化的功能分配框架很多,但大多面向固定的自动化水平进行分配。影响功能分配的因素很多,而且还存在可能的未知因素影响。未来月面人机联合探测涉及复杂任务和较多复杂的系统,如果人-自动化/机器人之间功能分配不合理,动态分配的机制设计人因考虑不足,对航天员注意力分配、不同自动化水平之间转换的时机和转换模式设计不足,将会影响航天员的工作负荷和情境意识、对自动化的信任/不信任、自满、技能退化和模式意识差等问题,进而导致系统安全性和效能降低[18]。未来月面人机联合探测,需要航天系统(如无人驾驶飞行器、机器人、漫游车和栖息地等)具备柔性和动态人机功能分配能力,能够根据航天员需求、环境特征、情境条件和突发事件等,对系统的自动化水平进行调整和响应。
月面任务的不确定性很高,应对自动化和机器人系统的脆弱性及其对航天员和任务的影响进行充分的分析考虑。自动化从本质上改变了航天员的作业性质。航天员和多种自动化之间存在多种权限和自主性分配,如果没有合理设计人机关系,并提高与自动化/机器人的透明度,以便航天员更好地理解自动化,将导致意图和状态误判、人机协同不畅,甚至人机冲突,危及航天员和航天系统安全。面对越来越高的航天系统自动化和智能化程度,如果航天员不能构建准确的心智模型,将导致在系统使用中出现自满及情境意识丧失。对于越来越复杂的自动化和机器人系统,如果其透明度设计不足,在系统失效需要航天员立即介入时,航天员将不具备必要的情境意识,导致难以介入或接管,并易引发人误。在未来月面人机联合探测中,航天器和装备的自动化和智能化程度将不断提升,对人机关系产生深刻影响,也给航天人因工程带来更多的研究课题。
在人机联合探测中,保持航天员对自动化和机器人系统适当的信任水平,对月面人机联合探测成功非常重要,既不能“过信任”,也不能“欠信任”。过信任将降低航天员情境意识,将所有决策控制权交给自动化系统或机器人,无法对未识别的危险或系统识别错误的危险作出响应;欠信任时航天员完全依靠自身进行操作,会极大增加航天员作业负荷。信任的影响因素很多,与人、机和环境都相关,而且与人机功能分配的要素交织在一起。面向未来的月面人机联合探测任务,如何厘清影响因素,如何建立合理信任水平,如何对信任进行合理的测量,如何正确校准信任等都面临挑战。如果没有很好地解决这些挑战,人机联合探测的成功实施将会受到影响。
月面人机联合探测将是多个航天员多个机器人的团队协作。如何使机器人安全地在航天员周围工作是人因设计面临的一个重要挑战。协作空间、协作模式和安全机制等设计不当,将引发航天员安全风险。需要深入理解人、机器人近距离工作时的相互关系,以及人类对安全的感知问题。受地月距离、通信延迟等制约,月面探测机器人的人机协同和交互设计挑战很大。关于遥操作、监督控制和人机团队合作的人因设计知识和经验还非常缺乏。如何将多个自动化系统、机器人和航天员整合,如何构建有效的团队共享心智模型、交互架构,如何提升人机互理解性和人机信任等都面临很大的技术挑战,解决不当会导致航天员作业负荷增加、系统失效和低效,危及航天员和航天系统安全[20]。
未来月面人机联合探测面临特殊的月面环境和复杂的任务。月面恶劣环境不仅对航天员能力特性产生很大影响,使得人-机器人团队协同整合设计难度加大,机器人系统也会面临很强的重量体积约束,需要对恶劣的环境(辐射、极端温度、照明变化和微流星体等)具有较强的适应性。机器人和它们的操作者(航天员或地面飞控人员)之间的距离不同。远距离传输延迟造成通信的间歇性,影响连续、大带宽的信号传输,会对人-机器人交互产生影响。未来月面人机联合探测任务复杂、类型多样,包括月面的科学探测、样本检测和收集、月球基地的建造和日常维护维修等。各类任务对航天员和机器人的需求差异很大。为确保航天员保持合理的工作负荷和情境意识水平,确保航天员安全和任务成功,在进行人-机器人协同设计时,需要考虑的问题包括如何确定合理的机器智能类型/方法/形式/数量;如何与数量有限的航天员合理进行角色和功能分配;如何从时间和空间维度对人-机器人进行整合设计,构建与各种任务场景、各种正常和异常工况匹配的人-机器人协同模式/体系架构/作业流程等。当前的基础数据和飞行经验不足,人因设计的相关理论和方法有限,现有的设计指南和有效性验证能力不足,都使得人-机器人协同设计面临巨大挑战。
为保证月面人机联合探测中航天员与自动化、智能化系统的有效整合,需在地面开展大量的人在回路的测试和试验,采集航天员(包括着登月服后)月面作业能力数据,开展航天员-机器人的协同与交互的关键影响因素研究,进行人机交互、人-机器人协同模式和任务流程等的测试和设计验证。为此,需要构建人在回路测试和试验的平台,对月面任务、月球相关环境特征(如低重力等)进行有效的、具有一定保真度的模拟,并支持人在回路的试验和数据测试。在地面上构建这样的平台难度很大,特别是1/6重力、月尘和光环境等的模拟。目前在地面上还没有一个能够全面模拟月球环境的设施。
NASA针对月面人机联合探测构建了一系列地面模拟测试平台[22],从不同维度对月面特征进行模拟,并针对探测任务中的系统研发和测试、任务设计和验证、人-系统整合测评等建立了方法和技术体系,但也存在一些局限性。例如,卸载系统可一定程度上实现对低重力环境的模拟,但其悬吊方式和吊具的设计对航天员运动影响很大,对于航天员着登月服后高动态、大范围的姿态变换支持能力有限;失重飞机利用抛物线飞行,能提供很好的低重力模拟,但时间只有20多秒,成本高且难以充分测试。面向未来的月面人机联合探测需要的大量人在回路测试和验证。如何深入认识不同测试环境对测试的约束和对测试数据的影响,如何提升地面测试方法的信度和效度,如何创建更好的地面模拟和人因测试技术,如何有效、高效整合各个地面模拟现场的测试数据,如何运用运动地面和飞行人因数据推动人因工程数字仿真能力提升等都是面临的重要挑战。
除了地面模拟环境面临的挑战外,人-机器人协同相关的人因试验方法也面临挑战。在人-机器人整合研究中,试验需要机器人能长时间可靠工作,并且变量要易于调整。另外,地面很难模拟各类机器人在太空和月面时的独特性。机器人与航天员或地面控制人员之间的匹配问题很难监测到。这些挑战要求未来面向月面人机联合探测应用创建人-机器人的人因研究和试验方法。
安全性和整体效能是人-机器人系统整合设计的关键。未来月面探测机器人的系统多样化,人机交互的模式差异大,智能化和自动化水平配置高度依赖于任务,导致航天员需要面对复杂多样的人-机器人协作、控制和交互方式,容易引发高负荷、人误、绩效下降和安全风险等。目前,尚缺乏一套综合、统一、有效的指标和规范体系对人-机器人系统的人因设计和评估进行指导和支持[23⇓-25]。针对未来月面人机联合探测中各类复杂任务和多种作业场景及大量多种类机器人,如何系统揭示任务独特需求及人-机器人协作中的交互性质;如何构建一套有效、通用化和覆盖各类人-机器人团队协同和交互模式的界面设计准则和指南;如何提高机器人意图和动作的一致性;如何确保人和机器人系统的信息共享,保持合适的信任水平和情境意识,降低错误和任务目标失败的风险,这些都是人因工程面临的全新挑战。
人机团队协同的人因设计验证与评估也面临全新的挑战,特别是针对团队协同、动态人机功能分配、多智能体的信息和知识共享、人机透明度、人机互信、异常状态下控制模式转换,以及人-机器人整合设计对航天员态势感知、工作负荷和任务绩效的影响等的评估,在评估指标、测试技术、评价方法和模型等方面都有很多问题需要解决[26]。
为有效应对未来月面人机联合探测所面临的人因学挑战,笔者从以下3方面提出对策建议。
首先,面向月面探测安全、高效的人机协同与交互需求,开展面向月面特因环境下航天员能力特性、人机联合探测的智能系统构成,以及以航天员为中心的人机团队和动态功能分配机制的人因工程基础理论、技术方法和工具等方面的规划和研究。突破人的能力特性变化监测、人机协同任务分配机制及人机交互界面设计等基础理论和方法,分析月面特因环境的影响和约束因素,研制基于人因设计的高效、安全人机协作、控制和交互方式,形成人因测试评估理论和方法。
其次,面向月面人机联合探测的试验和人因评估需求,研制面向月面特因环境的月面任务场景仿真和人机团队协同作业系统及其评估系统。突破月面特因环境的模拟、月面机器人测试和多维度人因量化指标的测试评估等关键技术,研制悬吊、水下、野外和仿真等多种模拟平台。载人航天工程应面向未来的研究需求,充分利用中国空间站在轨飞行平台,构建天地一体的月面人机联合探测人因研究、设计验证和评价的支撑平台,为多学科研究团队提供协同研究平台,也为探测中各类人-自动化/机器人/人工智能(AI)团队整合能力,提供通用的测试和评估支撑平台。
最后,面向月面探测的人-系统整合设计与评估规范、标准与方法需求,在载人航天装备和系统研发全周期,从技术和管理两个层面进一步加大人-系统整合力度。月面人机联合探测中人因问题的解决,需要机器人技术、航天器系统设计和人因工程等多学科团队协同;需要采用跨学科方法才能构建有效的解决方案;需要进一步优化航天系统研发技术和管理流程;加强在系统工程层面的人因研究和人因设计的早期应用和持续快速迭代;加强设计研发中多学科团队的配置和有效协同机制建立;加强以人为中心的AI设计;加强相应的人因设计规划和标准研究等[27]。如此才能研发出更好、更有效的航天系统和装备,为未来人机联合探测打下坚实基础。
在未来载人月球探测活动中,航天员-自动化/机器人协同将是主要模式,但要有效利用人机团队,充分发挥航天员、自动化系统和机器人等智能系统各自的优势,解决人-自动化/机器人整合面临的大量人因问题和挑战。一要加大相关人因学基础理论、方法、技术和平台的研究布局和支持。二要加大对月面人机联合探测中人-系统整合技术和管理力度,创建有效性、通用性的人因评价指标、方法和技术。三要加大对月球特因环境的地面模拟和人因量化测试和分析技术研究,同时充分利用中国空间站在轨飞行平台,构建天地一体的月面人机联合探测人因研究、设计验证和评价的支撑平台,为中国未来载人月球探测提供重要支撑。中国在载人航天领域,已建立一套载人航天工效学的技术和管理体系[6,17],在中国空间站的研制和建造中发挥了重要作用。该体系及相应的航天人因工程理论、方法对于未来的月面人机联合探测也将发挥重要作用。
  • 国家自然科学基金(T2192933)
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doi: 10.3981/j.issn.2097-0781.2024.01.002
  • 接收时间:2023-08-18
  • 出版时间:2024-03-20
  • 发布时间:2024-03-27
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  • 收稿日期:2023-08-18
  • 修回日期:2024-01-10
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国家自然科学基金(T2192933)
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    中国航天员科研训练中心人因工程全国重点实验室,北京 100094

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表12种不同金属材料的力学参数
科
Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)
属
Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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