Chair's Distinguished Lecture: Abstractions for Robot Code

Sayan Mitra
Professor of Electrical and Computer Engineering
University of Illinois at Urbana-Champaign

Distributed robotics is poised to transformed manufacturing, transportation, agriculture, delivery, and exploration. Following the trends in cloud, mobile, and machine learning applications, finding the right programming abstractions is key in unlocking this potential. A robot's code needs to sense the environment, control the hardware, and communicate with other robots. Current programming languages do not provide the necessary hardware platform-independent abstractions, and therefore, developing robot applications require detailed knowledge of signal processing, control, path planning, network protocols, and various platform-specific details. Further, porting applications across hardware platforms becomes tedious. In this talk, I will present our recent explorations in finding good abstractions for robot code. The end result of our research is a new language called Koord which abstracts platform-specific functions for sensing, communication, and low-level control and makes platform-independent control and coordination code portable and modularly verifiable.

About the speaker...

Sayan Mitra is a Professor of Electrical and Computer Engineering at the University of Illinois at Urbana-Champaign. His research is centered around safe autonomy. He holds a PhD from MIT, MSc from the Indian Institute of Science, Bangalore, and an undergraduate degree in Electrical Engineering from Jadavpur University, Kolkata. Sayan was a postdoctoral fellow at CalTech, and held visiting faculty positions at Oxford University, TU Vienna, and Kirtland Air Force Research Laboratory. At Illinois, his research group has created a number of the leading software tools for programming and verification of autonomous systems and have authored more than one hundred peer reviewed articles. A textbook authored by Sayan “Verifying cyber-physical systems: A path to safe autonomy” will be published by the MIT Press in February 2021. Sayan’s work has been recognized by the National Science Foundation's CAREER Award in 2011, AFOSR Young Investigator Research Program Award in 2012, IEEE-HKN C. Holmes MacDonald Outstanding Teaching Award (2013), a RiSE Fellowship, a Siebel Fellowship, and several best paper awards.