Seminar
Carnegie Mellon University
Lesson Learned from Two Decades of Robotics Development and Thoughts on Where We Go from Here
Abstract: In this talk, Herman Herman will offer various lessons learned from developing various robots for the last 2 decades at the National Robotics Engineering Center. He will also offer his perspective on the future of autonomous robots in various industries, including self-driving cars, material handling and consumer robotics. Bio: Dr. Herman Herman is the [...]
Factor Graphs for Robot Perception
Abstract: Factor graphs have become a popular tool for modeling robot perception problems. Not only can they model the bipartite relationship between sensor measurements and variables of interest for inference, but they have also been instrumental in devising novel inference algorithms that exploit the spatial and temporal structure inherent in these problems. I will overview [...]
Towards better methods of video generation
Abstract: Learning to generate future frames of a video sequence is a challenging research problem with great relevance to reinforcement learning, planning and robotics. Existing approaches either fail to capture the full distribution of outcomes, or yield blurry generations, or both. In this talk I will address two important aspects of video generations: (i) what [...]
Light-Sensitive Displays
Abstract: Nobel prize winner M. G. Lippmann described his dream of an ideal display as a “window into the world.” “While the current most perfect photographic print only shows one aspect of reality, reduced to a single image fixed in a plane, the direct view of reality offers, as we know, infinitely more variety.” Changing [...]
Acquiring and Transferring Generalizable Vision-based Robot Skills
Abstract: In recent years, there have been great advances in policy learning for goal-oriented agents. However, there are still major challenges brought by real-world constraints for teaching highly generalizable and versatile robot policies in a cost efficient and safe manner. In this talk, I will argue that instead of aiming to teach large motion repertoires [...]
Learning to localize and anonymize objects with indirect supervision
Abstract: Computer vision has made great strides for problems that can be learned with direct supervision, in which the goal can be precisely defined (e.g., drawing a box that tightly-fits an object). However, direct supervision is often not only costly, but also challenging to obtain when the goal is more ambiguous. In this talk, I [...]
What People See in a Robot: A New Look at Human-Like Appearance
Abstract: A long-standing question in HRI is what effects a robot’s human-like appearance has on various psychological responses. A substantial literature has demonstrated such effects on liking, trust, ascribed intelligence, and so on. Much of this work has relied on a construct of uni-dimensional low to high human-likeness. I introduce evidence for an alternative view according to which [...]
Safe Learning in Robotics
Abstract: A great deal of research in recent years has focused on robot learning. In many applications, guarantees that specifications are satisfied throughout the learning process are paramount. For the safety specification, we present a controller synthesis technique based on the computation of reachable sets, using optimal control and game theory. In the first part [...]