Humans effortlessly push, pull, and slide objects, fearlessly reconfiguring clutter, and using physics and the world as a helping hand. But most robots treat the world like a game of pick-up-sticks: avoiding clutter and attempting to rigidly grasp anything they want to move. I'll talk about some of our ongoing efforts at harnessing physics for nonprehensile manipulation, and the challenges of deploying our algorithms on real physical systems. I'll specifically focus on whole-arm manipulation, state estimation for contact manipulation, and on closing the feedback loop on nonprehensile manipulation.
Speaker: Siddhartha Srinivasa is the Finmeccanica Associate
Professor at The Robotics Institute at Carnegie Mellon University. He works on
robotic manipulation, with the goal of enabling robots to perform complex manipulation
tasks under uncertainty and clutter, with and around people. To this end, he
founded and directs the Personal Robotics Lab, and co-directs the Manipulation
Lab. He has been a PI on the Quality of Life Technologies NSF ERC, DARPA ARM-S
and the CMU CHIMP team on the DARPA DRC.
Sidd is also passionate about building end-to-end systems (HERB, ADA, HRP3, CHIMP, Andy, among others) that integrate perception, planning, and control in the real world. Understanding the interplay between system components has helped produce state of the art algorithms for object recognition and pose estimation (MOPED), and dense 3D modeling (CHISEL, now used by Google Project Tango).Sidd received a B.Tech in Mechanical Engineering from the Indian Institute of Technology Madras in 1999, an MS in 2001 and a PhD in 2005 from the Robotics Institute at Carnegie Mellon University. He played badminton and tennis for IIT Madras, captained the CMU squash team, and likes to run ultra marathons.