Events Calendar

CS Distinguished Lecture: Tomas Lozano-Perez (MIT) - Generalization in Planning and Learning for Robotic Manipulation

Speaker: Tomas Lozano-Perez, Massachusetts Institute of Technology (MIT)

Talk Title: Generalization in Planning and Learning for Robotic Manipulation

Series: Computer Science Distinguished Lecture Series

Abstract: An enduring goal of AI and robotics has been to build a robot capable of robustly performing a wide variety of tasks in a wide variety of environments; not by sequentially being programmed (or taught) to perform one task in one environment at a time, but rather by intelligently choosing appropriate actions for whatever task and environment it is facing. This goal remains a challenge. In this talk I'll describe recent work in our lab aimed at the goal of general-purpose robot manipulation by integrating task-and-motion planning with various forms of model learning. In particular, I'll describe approaches to manipulating objects without prior shape models, to acquiring composable sensorimotor skills, and to exploiting past experience for more efficient planning.

Register in advance for this webinar at:

https://usc.zoom.us/webinar/register/WN_K4eWcqebRsWT20GhOAbi-g

After registering, attendees will receive a confirmation email containing information about joining the webinar.

This lecture satisfies requirements for CSCI 591: Research Colloquium.


Biography: Tomas Lozano-Perez is professor in EECS at MIT, and a member of CSAIL. He was a recipient of the 2011 IEEE Robotics
Pioneer Award and a co-recipient of the 2021 IEEE Robotics and Automation Technical Field Award. He is a Fellow of the AAAI, ACM, and IEEE.


Host: Stefanos Nikolaidis

Webcast: https://usc.zoom.us/webinar/register/WN_K4eWcqebRsWT20GhOAbi-g

Location: Online - Zoom Webinar

WebCast Link: https://usc.zoom.us/webinar/register/WN_K4eWcqebRsWT20GhOAbi-g

Audiences: Everyone Is Invited

Contact: Computer Science Department

This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor.