Reimagining Robots

Duration: 1 hour 23 mins

Share this media item:

Embed this media item:

<iframe width="_width_" height="_height_" src="https://sms.cam.ac.uk/media/3565279/embed" frameborder="0" scrolling="no" allowfullscreen></iframe>

Choose size:

About this item

Available Formats

About this item

Description:	The 2021 Annual Wheeler Lecture in the Dept of Computer Science and Technology, given by Prof Daniela Rus on Wednesday 12th May 2021.


Created:	2021-06-23 11:00
Collection:	Annual Wheeler lectures
Publisher:	University of Cambridge
Copyright:	Dept of Computer Science and Technology
Language:	eng (English)
Keywords:	Computer Science; robots; Wheeler Lecture;


Abstract:	The digitisation of practically everything coupled with advances in machine learning, the automation of knowledge work, and advanced robotics promises a future with democratised use of machines and wide-spread use of AI, robots and customization. While the last 60 years have defined the field of industrial robots, and empowered hard bodied robots to execute complex assembly tasks in constrained industrial settings, the next 60 years could be ushering in our time with pervasive robots that come in a diversity of forms and materials, helping people with physical and cognitive tasks. However, the pervasive use of machines remains a hard problem. How can we accelerate the creation of machines customized to specific tasks? Where are the gaps that we need to address in order to advance the bodies and brains of machines? How can we develop scalable and trustworthy reasoning engines? In this talk I will discuss recent developments in machine learning and robotics, focusing on about how computation can play a role in: * developing Neural Circuit Policies, an efficient approach to more interpretable machine learning engines, * making machines more capable of reasoning in the world, * making custom robots, and * making more intuitive interfaces between robots and people."

Abstract:

The digitisation of practically everything coupled with advances in machine learning, the automation of knowledge work, and advanced robotics promises a future with democratised use of machines and wide-spread use of AI, robots and customization. While the last 60 years have defined the field of industrial robots, and empowered hard bodied robots to execute complex assembly tasks in constrained industrial settings, the next 60 years could be ushering in our time with pervasive robots that come in a diversity of forms and materials, helping people with physical and cognitive tasks. However, the pervasive use of machines remains a hard problem.

How can we accelerate the creation of machines customized to specific tasks? Where are the gaps that we need to address in order to advance the bodies and brains of machines? How can we develop scalable and trustworthy reasoning engines? In this talk I will discuss recent developments in machine learning and robotics, focusing on about how computation can play a role in:

* developing Neural Circuit Policies, an efficient approach to more interpretable machine learning engines,

* making machines more capable of reasoning in the world,

* making custom robots, and

* making more intuitive interfaces between robots and people."

Available Formats

Format	Quality	Bitrate	Size
MPEG-4 Video	1280x720	2.97 Mbits/sec	1.81 GB	View
MPEG-4 Video	640x360	1.79 Mbits/sec	1.09 GB	View
WebM	1280x720	3.02 Mbits/sec	1.84 GB	View
WebM	640x360	1.12 Mbits/sec	700.69 MB	View
iPod Video	480x270	490.5 kbits/sec	298.18 MB	View
MP3	44100 Hz	249.92 kbits/sec	153.76 MB	Listen
Auto *	(Allows browser to choose a format it supports)