RobCE 2024
听众征集
听众征集:注册成功的听众可以参加会议的所有分会,你可以获得和机器人等领域的专家面对面交流的机会,获得专家的指点并提升自己的专业能力,顺便还可以欣赏爱丁堡的美景!机会不容错过。
微信咨询号
扫码咨询周老师
会议日程:
以上日程为简要情况,具体请以会前发送的文件为准
会议地点—爱丁堡龙比亚大学
爱丁堡龙比亚大学是苏格兰排名第一的现代大学(出自2024年世界大学排名)。它还是苏格兰现代大学中研究能力和研究影响力最高的大学(出自REF 2021),也是英国职业前景排名前五的现代大学(出自卫报大学指南2024)。
它在爱丁堡有三个校区,为来自世界各地的学生们提供先进的学习、教学和研究设施。爱丁堡龙比亚大学坐落在一个标志性的、繁荣的城市,是一个居住、工作和学习的好地方。(https://www.napier.ac.uk/)
爱丁堡有着悠久的历史,完好保存了许多历史建筑。爱丁堡城堡、荷里路德宫、圣吉尔斯大教堂等名胜都位于此地。爱丁堡的旧城和新城一起被联合国教育、科学及文化组织列为世界遗产。2004年爱丁堡成为世界第一座文学之城。爱丁堡的教育也很发达,英国最古老的大学之一爱丁堡大学就坐落于此,现在还是世界顶尖名校。根据2023年QS世界大学排名的数据,爱丁堡大学排名世界第15位,位列苏格兰地区第一,英国第五。加上爱丁堡国际艺术节等文化活动,爱丁堡成为了仅次于伦敦的英国第二大旅游城市。
国内直飞航班推荐:
海南航空目前已开通北京首都国际机场直飞至爱丁堡国际机场
去程:计划03:10从北京首都国际机场起飞,07:00到达爱丁堡机场,飞行时长10小时50分钟;
返程:英国时间12:00从爱丁堡起飞,次日05:10到达北京,飞行时长10小时10分钟。
图源:海南航空官网
官网上可以看到今年的航班班期:
6月24日至9月30日班期为:每周一、三、五、六
*具体执飞日期和价格可能变化,以海南航空官网为准。
爱丁堡机场—爱丁堡龙比亚大学(Craiglock Heart Campus)
公交:爱丁堡机场(步行大约3分钟)→Terminal Forecourt (Stop C)→Elliot Place(共33站)→爱丁堡龙比亚大学(Craiglock Heart Campus)(步行大约8分钟)
公交:爱丁堡机场(步行大约3分钟)→Terminal Forecourt (Stop C)→Gyle Centre (Stop KB)(共6站,换乘公交36号)→Glenlockhart Bank(共19站)→爱丁堡龙比亚大学(Craiglock Heart Campus)(步行大约2分钟)
地铁+公交:爱丁堡机场(步行大约4分钟)→Edinburgh Airport→Edinburgh Park Station(共6站)→Hermiston Gait(换乘公交36号)→Glenlockhart Bank(共15站)→爱丁堡龙比亚大学(Craiglock Heart Campus)(步行大约2分钟)
机场快线+公交:爱丁堡机场(步行大约3分钟)→Airport (Stop E)→Shandwick Place (Stop SC)(共4站)→Lothian Road (Stop XE)(步行约3分钟,换乘公交10号)→Craiglockhart Campus(共17站)→爱丁堡龙比亚大学(Craiglock Heart Campus)(步行大约4分钟)
Shane Xie 教授
英国利兹大学
Shane Xie教授在机器人和外骨骼领域拥有超过30年的研究经验。他是IEEE/ASME Transactions on Mechatronics的技术编辑,也是International journal of Biomechatronics and Biomedical Robotics的主编,还是新西兰工程学会院士、IEEE院士、ASME院士和英国机械工程师学会院士。
报告标题:Advanced Robotics with Enhanced Autonomy and Intelligence for Effective Medical Rehabilitation
摘要:Globally, 15M people suffer a stroke every year, causing 6M deaths and leaving another 5M permanently disabled, which makes stroke the second leading cause of disability worldwide . In the UK, strokes affect over 152,000 Britons each year. Currently, there are over 1.2 million people living with the effects of stroke in the UK, and the estimated direct and indirect costs of stroke care for the NHS are >£9 billion a year. According to UK Guidelines for stroke rehabilitation, patients should receive at least 45 minutes of therapy per day for a minimum of 5 days per week; however, this standard has never been met due to the deceasing availability of rehabilitation services and increasing pressure on the NHS. In the UK, there are > 600,000 stroke patients that live further than 20km from a stroke support group, and the majority of them have severe mobility issues, it would be very challenging and costly, or even impossible for them to travel and receive regular rehabilitation treatment in hospitals or rehabilitation centers. The NHS' Five Year Forward View made recommendations in 2017 to bring rehabilitation to people in their own homes and care homes.
This talk will discuss the key societal challenges and robotic technologies for delivering effective care and opportunities for the healthcare industry. It will cover the recent development of robotics for stroke rehabilitation, the research gaps and the need for new technologies in neuroscience, robotics, control and artificial intelligence. The talk will also introduce a EPSRC-funded project on intelligent reconfigurable exoskeletons tailored to meet patients’ needs, deliver effective diagnosis and personalised treatment, and monitored remotely by rehabilitation therapists. The key projects conducted at the Leeds Centre for Assistive/Rehabilitation Robotics will be introduced including peanumatic Peano muscle, DEA, soft exoskeleton, bilaterial robot, neuromuscular and brain computer interfaces. The focus is placed on the enabling technologies for those whose strength and coordination have been affected by amputation, stroke, spinal cord injury, cerebral palsy and ageing.
丁正桃 教授
英国曼彻斯特大学
英国曼彻斯特大学电气与电子工程学院控制系统首席教授,中英先进控制联合实验室主任,控制和机器人小组负责人。主持多个英国基金委和工业界的项目。研究兴趣包括非线性和自适应控制理论及其应用,最近的研究兴趣是基于网络的控制,分布式优化和分布式学习,以及在电力系统和机器人学中的应用。
报告标题:Cooperative and Finite-Time Formation Control of Autonomous Robots and Vehicles
摘要:In this network-connected world, many tasks require coordination and cooperation of subsystems/agents via network connection. Multi-agent systems are good examples of interplay between network communication and control applications. Finite-time control and finite-time mechanisms have been significantly developed to ensure the convergence of controlled variables in finite-time, and hence it is very appealing to various applications, including cooperative control of autonomous systems such as robotics and vehicles. This talk will briefly review some fundamental concepts of multi-agent systems and finite-time control mechanisms, and their further developments in engineering applications. It will then focus on formation and cooperative control mobile robots and autonomous vehicles. In particular, the talk will cover in details of some important methods, such as affine and bearing-only formation control algorithms which rely on the stress matrices and bearing. It will also cover distributed motion control algorithms to ensure autonomous overtaking of autonomous vehicles in a dynamic environment using the Artificial Potential Field (APF) method based on a robust autonomous vehicle platoon system.
United Kingdom
周老师
19150357586
HKSME15756362251
info_robce@vip.163.com
https://www.robce.org
陈老师
19160368706
(微信同号)