For intelligent robots to become ubiquitous, we need to "solve" locomotion, navigation and manipulation at sufficient reliability in widely varying environments. Learning approaches have been responsible for most recent advances, but they are held up by the lack of "big data" at the scale available in language and vision. In my talk, I will showcase recent research results on all three tasks. In locomotion, following past work on quadrupeds, we now have demonstrations of humanoid walking in a variety of challenging environments. In navigation, we pursued the task of "Go to Any Thing" -– a robot, on entering a newly rented Airbnb, should be able to find objects such as TV sets or potted plants. In manipulation we studied dexterous dynamic tasks such as in-hand rotation and twisting off caps of bottles. RL in simulation and sim-to-real have been workhorse technologies for us, assisted by a few technical innovations. For dexterous manipulation, multimodal perception is key – vision, touch and proprioception. The ability to exploit visual imitation would go a long way to solving the big data problem, and we have made major progress on the prerequisite steps of 4D reconstruction of human bodies, hands, and manipulable objects.

Bio

Jitendra Malik is Arthur J. Chick Professor of EECS at UC Berkeley, and (part-time) Research Scientist Director at FAIR, Meta Inc. His group has conducted research on many different topics in computer vision, computer graphics, machine learning and robotics resulting in concepts such as anisotropic diffusion, high dynamic range imaging, normalized cuts, R-CNN and rapid motor adaptation. His publications have received eleven best paper awards, including six test of time awards - the Longuet-Higgins Prize for papers published at CVPR (three times) and the Helmholtz Prize for papers published at ICCV (three times). He has mentored more than 80 PhD students and postdoctoral fellows, many of whom have gone on to become leading researchers at places like MIT, Berkeley, CMU, Caltech, Cornell, UIUC, UPenn, Michigan, UT Austin, Google and Meta.

Jitendra received the 2016 ACM/AAAI Allen Newell Award, 2018 IJCAI Award for Research Excellence in AI, and the 2019 IEEE Computer Society’s Computer Pioneer Award for “leading role in developing Computer Vision into a thriving discipline through pioneering research, leadership, and mentorship”. He is a member of the National Academy of Sciences, the National Academy of Engineering and Fellow, American Academy of Arts and Sciences.

This talk will be streamed live on our YouTube channel. Link will be available on that page one hour prior to the event.