Abstract

In the last few decades, most robotics success stories have been limited to structured or controlled environments. These include manufacturing, industrial applications, fulfillment & warehouses, autonomous driving on roads with low traffic, etc. A major challenge is to develop robot systems that can operate in complex or unstructured environments corresponding to construction, city streets, delivery scenarios, etc. Recent developments in machine learning, computer vision, planning, manipulation and control technologies are resulting in development of next generation robotics systems that can operate in uncontrolled environments. In this talk, we will give a brief overview of our recent work on combining these techniques for complex applications: robot navigation in crowded indoor environments or outdoor scenes, autonomous driving in dense, heterogeneous traffic scenarios, and an autonomous excavation that can continuously operate for 24 hours without any human assistance. 

Biography

Dinesh Manocha is Paul Chrisman-Iribe Chair in Computer Science & ECE and Distinguished University Professor at University of Maryland College Park. His research interests include virtual environments, physically-based modeling, and robotics. His group has developed a number of software packages that are standard and licensed to 60+ commercial vendors. He has published more than 600 papers & supervised 40 PhD dissertations. He is a Fellow of AAAI, AAAS, ACM, and IEEE, member of ACM SIGGRAPH Academy, and Bézier Award from Solid Modeling Association. He received the Distinguished Alumni Award from IIT Delhi the Distinguished Career in Computer Science Award from Washington Academy of Sciences. He was a co-founder of Impulsonic, a developer of physics-based audio simulation technologies, which was acquired by Valve Inc in November 2016.

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https://live.bilibili.com/22051279