多智能体强化学习用于多机器人安全导航方向博士研究员
Multi-agent reinforcement learning for safe navigation of multiple robots
原帖优先：申请材料、截止时间与资格以原帖和学校官方说明为准。
博士招生与资助公告
- 申请年度
- 2027；原帖说明：How to apply Apply now You need to: • choose programme type (Research), 2027/28, Faculty of Engineering and Physical Sciences • select Full time or Part time • search for programme PhD Computer Science (7089) • add name of the supervisor in section 2 of the application Applications should include: • research proposal • your CV (resumé) • 2 academic references • degree transcripts and certificates to date • English language qualification (if applicable)
- 最近申请截止
- 2027-08-31
- 全部申请截止
- （Europe/London）
- 资助原文
- Fees and funding We offer a range of funding opportunities for both UK and international students. Horizon Europe fee waivers automatically cover the difference between overseas and UK fees for qualifying students. Competition-based Presidential Bursaries from the University cover the difference between overseas and UK fees for top-ranked applicants. Competition-based studentships offered by our schools typically cover UK-level tuition fees and a stipend for living costs for top-ranked applicants. Funding will be awarded on a rolling basis, so apply early for the best opportunity to be considered. For more information, please visit our postgraduate research funding pages.
- 资助条件
- 原帖为竞争性或附条件资助说明，未确认本项目获资助及申请人能获奖；不作为保证全奖。
- 原帖材料说明
- • research proposal
- • your CV (resumé)
- • 2 academic references
- • degree transcripts and certificates to date
- • English language qualification (if applicable)
确定性信息来自对应版本的完整原帖。原帖只提供日期，日末和学校当地时区为本站转换假设。筛选使用最后申请截止；资助与录取以学校审核结果为准。
AI 中文速览
- 研究内容
- 本项目研究共享空间中多机器人的以人为中心的协调，探索多机器人如何在追求集体任务的同时，根据不同人群的存在调整其行为，考虑个人偏好、舒适区、社会期望和不断变化的人类行为。研究可能结合多智能体强化学习、人机交互、机器人导航以及人类实验研究，并利用SooratiLab中的机器人狗、地面巡视车、四轴飞行器和机械臂等机器人平台进行模拟和物理平台验证。
- 申请条件
- 申请人必须持有计算机科学、机器人学、人工智能、工程学、人机交互、心理学、认知科学或密切相关学科的英国2:1荣誉学位或国际同等学历。必备技能包括：具备机器学习技术（包括强化学习）的良好背景；对人机交互、自主系统、机器人学或人工智能有浓厚兴趣；能够独立开展研究并批判性评估科学文献；具备扎出的编程技能（优选Python或同类语言）。
- 待遇
- 学校为英国和国际学生提供一系列资助机会，竞争性总统奖学金可为顶级申请者涵盖海外学费与英国学费之间的差额，学院提供的竞争性学生奖学金通常涵盖英国水平的学费及生活津贴，资助以滚动方式授予。
- 申请方式
- 申请人需选择项目类型（Research），2027/28学年，工程与物理科学学院（Faculty of Engineering and Physical Sciences），选择全职或兼职，搜索PhD Computer Science (7089)项目，并在申请表的第二部分添加导师姓名。
- 材料清单
- 研究计划书 (research proposal)
- 简历 (your CV (resumé))
- 2封学术推荐信 (2 academic references)
- 迄今为止的学位成绩单和证书 (degree transcripts and certificates to date)
- 英语语言资格证明（如适用） (English language qualification (if applicable))
由 gemini-2.5-flash-lite 生成，博士岗判定置信度 100%。
岗位信息
- 最终轮次截止
- 2027-08-31
- 学科
- 计算机科学
- 合同类型
- 项目资助
- 本站收录
- 内容更新
- 导师
- Dr Mohammad Soorati
- 来源
- 南安普顿大学博士研究项目招生 · 最近核对 2026-10-10
- 详情核验
判定依据（原文摘录）
- is_phd
Type of degree Doctor of Philosophy
- english_ok
English language qualification (if applicable)
- bachelor_ok
You must have a UK 2:1 honours degree, or its international equivalent
原文
View all current projects
Postgraduate research project
Multi-agent reinforcement learning for safe navigation of multiple robots
Funding
Competition funded
Competition funded
View fees and funding
Type of degree
Doctor of Philosophy
Entry requirements
2:1 honours degree
2:1 honours degree
View full entry requirements
Faculty graduate school
Faculty of Engineering and Physical Sciences
Closing date
31 Aug 2027
On this page
About the project
Potential supervisors
Entry requirements
Fees and funding
How to apply
Contact us
About the project
Potential supervisors
Entry requirements
Fees and funding
How to apply
Contact us
About the project
As robot swarms increasingly operate alongside people, robots must do more than avoid collisions. They must behave in ways that people find safe, predictable and comfortable. This project investigates how multiple robots can coordinate their collective goals while adapting their behaviour to individual humans, preferences and social expectations in shared spaces.
Robot swarms could support people in homes, workplaces, hospitals and public spaces, but operating safely around humans requires more than collision avoidance. Robots must balance their own objectives with the safety, comfort, expectations and trust of the people sharing their environment.
This project investigates human-centred coordination for multiple robots operating in shared spaces. The research explores how multiple robots can pursue collective tasks while adapting their behaviour to the presence of different people. Rather than treating humans simply as obstacles, the project investigates how robots can account for individual preferences, comfort zones, social expectations and changing human behaviour when deciding where and how to move.
Building on existing work using decentralised multi-agent reinforcement learning for navigation around multiple humans, the project explores questions such as:
• how should a swarm trade off task efficiency against human comfort?
• how can robots learn individual differences in acceptable proximity and behaviour?
• how should robots coordinate when accommodating one person's preferences affects the swarm's task?
• how can a swarm communicate its intentions so that people understand and trust its behaviour?
The research may combine multi-agent reinforcement learning, human-robot interaction, robot navigation and experimental studies with humans, using simulation and physical robot platforms. You'll have opportunities to develop and evaluate novel algorithms and interaction strategies for safe, socially acceptable and trustworthy robot swarms operating in real-world environments. You'll have access to the robotic platforms available in SooratiLab including robot dogs, several ground rovers, quadcopters, robotic arms, etc.
The School of Electronics and Computer Science is committed to promoting equality, diversity inclusivity as demonstrated by our Athena SWAN award. We welcome all applicants regardless of their gender, ethnicity, disability, sexual orientation or age, and will give full consideration to applicants seeking flexible working patterns and those who have taken a career break. The University has a generous maternity policy, onsite childcare facilities, and offers a range of benefits to help ensure employees’ well-being and work-life balance. The University of Southampton is committed to sustainability and has been awarded the Platinum EcoAward.
Potential supervisors
Lead supervisor
Dr Mohammad Soorati
Dr.Eng., MSc, BSc
Associate Professor
Research interests
• Human-swarm Interaction
• Multi-robot Systems
• Swarm Robotics
Entry requirements
You must have a UK 2:1 honours degree, or its international equivalent, in one of the following:
• computer science
• robotics
• artificial intelligence
• engineering
• human-computer interaction
• psychology
• cognitive science
• a closely related discipline
Essential skills:
• good background in machine learning technogolies including reinforcement learning
• strong interest in human-robot interaction, autonomous systems, robotics or artificial intelligence
• ability to undertake independent research and critically evaluate scientific literature
• strong programming skills, preferably in Python or a comparable language
Fees and funding
We offer a range of funding opportunities for both UK and international students. Horizon Europe fee waivers automatically cover the difference between overseas and UK fees for qualifying students.
Competition-based Presidential Bursaries from the University cover the difference between overseas and UK fees for top-ranked applicants.
Competition-based studentships offered by our schools typically cover UK-level tuition fees and a stipend for living costs for top-ranked applicants.
Funding will be awarded on a rolling basis, so apply early for the best opportunity to be considered.
For more information, please visit our postgraduate research funding pages.
How to apply
Apply now
You need to:
• choose programme type (Research), 2027/28, Faculty of Engineering and Physical Sciences
• select Full time or Part time
• search for programme PhD Computer Science (7089)
• add name of the supervisor in section 2 of the application
Applications should include:
• research proposal
• your CV (resumé)
• 2 academic references
• degree transcripts and certificates to date
• English language qualification (if applicable)
Contact us
Faculty of Engineering and Physical Sciences
For questions about applying, email our Doctoral College (doctoralcollege-admissions@soton.ac.uk).
Project leader
For an initial conversation, email Dr Mohammad Soorati (M.Soorati@soton.ac.uk).