Scaling Sim2Real Learning For Robotic Rearrangement

Date:  3/9/23

Speaker:  Adithyavairavan Murali

Location: Zoom

Time: 2:40 p.m.-3:30 p.m.

AbstractAdithya Murali is a scientist at the NVIDIA Robotics research team. He received his PhD at the Robotics Institute, Carnegie Mellon University, where he was supported by the Uber Presidential Fellowship. During his PhD, he also spent time at Meta AI Research where he led the development of the and low-cost robot projects. His work has been a Best Paper finalist at ICRA 2015 and 2020 and has been covered by WIRED, the New York Times, etc. His general interests are in robotic manipulation, 3D vision, synthetic content generation and learning.

Bio:  Rearrangement is a fundamental task in robotic manipulation and which when solved, will help us to achieve the dream of robot butlers working seamlessly in human spaces like homes, factories and hospitals. In this talk I’ll be presenting some recent work in 3D synthetic content generation and new approaches for neural motion planning. Training models from this large-scale simulated data allows us to generalize directly to rearrangement in the real world from just raw camera observations as input, without training on any real data.