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学术报告《机器人计算时代的机遇》

发布日期:2022/03/17 点击量:

报告题目:机器人计算时代的机遇 Opportunities in the Era of Robotic Computing

报 告 人 :刘少山 智能机器人公司PerceptIn创始人 加利福尼亚大学(尔湾)博士

报告时间:2022-03-22 09:00

报告地点:腾讯会议855-8495-5027


Abstract:

The commercialization of autonomous machines is a thriving sector, and likely to be the next major computing demand driver, after PC, cloud computing, and mobile computing. Nevertheless, a suitable computing system, a powerful compiler, an operating system, and a distributed system for autonomous machines are missing, and many companies are forced to develop ad hoc computing solutions that are neither scalable nor extensible. In this talk, we share our experiences of building computing systems for autonomous machines, including on-machine computing systems, cloud computing systems, and cooperative autonomous machine computing systems (e.g. multi robots). We summarize our key findings and explore how to build computing systems to guarantee the real-time performance, reliability, safety, and security of autonomous machines.

Based on our experiences, we also make a few technology predictions.

1. This generation of robotic computing systems should be defined by China, where the supply chain as well as the industry are located.

2. An architecture for robots will soon become clear.

3. A new language to describe robot behavior will emerge on this robot computing architecture.

4. A new robot operating system will take shape with the mass shipment of robots, most likely starting with two industries: autonomous electric vehicles, or robot vacuums.

5. Cooperative autonomous driving, multi-robot collaboration will produce a robotic distributed system similar to Map-Reduce.


机器人的商业化是一个蓬勃发展的领域,并可能成为继个人电脑、云计算和移动计算之后的下一个主要计算需求驱动力。然而,一个合适的计算系统、一个强大的编译器、一个操作系统和一个用于自主机器的分布式系统是缺失的,许多公司被迫开发临时的计算解决方案,这些解决方案既不具有可扩展性也不具有可延伸性。在本讲座中,我们将分享我们为机器人(包括无人车)构建计算系统的经验,包括机上计算系统、云计算系统和合作式机器人计算系统(如多机器人)。 我们总结了我们的主要发现,并探讨了如何构建计算系统以保证自主机器的实时性能、可靠性、安全性和安全性。

基于我们的经验,我们也做了一些技术预测。

1. 这一代的机器人计算系统应该由中国来定义,因为中国是供应链以及产业的所在地。

2. 一种机器人计算的的计算机体系结构将很快变得清晰。

3. 一种描述机器人行为的新语言将在这个机器人计算架构上出现。

4. 一个新的机器人操作系统将随着机器人的大规模出货而形成,最有可能从两个行业开始:自主电动汽车,或机器人吸尘器。

5. 合作式自主驾驶、多机器人协作将产生一个类似于Map-Reduce的机器人分布式系统。


Biography:

Dr. Shaoshan Liu is the founder of PerceptIn Inc, an intelligent robotics company. Shaoshan Liu's technical research focuses on Autonomous Driving technologies and Robotics. He has published over 100 research papers, 40 U.S. patents, and over 150 international patents. Dr. Shaoshan Liu have published three books on robotics technologies "Creating Autonomous Vehicle Systems (Morgan & Claypool)", "Engineering Autonomous Vehicles and Robots: The DragonFly Modular-based Approach (Wiley - IEEE)", and "Robotic Computing on FPGAs (Morgan & Claypool)" Dr. Shaoshan Liu was a founding member of Baidu USA, where he built the Autonomous Driving Systems team, and performed R&D work at LinkedIn, Microsoft, Microsoft Research, INRIA, Intel Research, and Broadcom. He is a senior member of IEEE, a Distinguished Speaker of the IEEE Computer Society, a Distinguished Speaker of the ACM, and a founder of the IEEE Special Technical Community on Autonomous Driving Technologies. Dr. Shaoshan Liu received a Master of Public Administration (MPA) from Harvard Kennedy School, and a Ph.D. in Computer Engineering from University of California, Irvine.



邀请人:张伟

审核人:王美琴


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