Calendar of Events
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1 event,
VASC Seminar
Fereshteh Sadeghi
Computer Science, University of Washington
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 [...]
1 event,
PhD Speaking Qualifier
Adithyavairavan Murali
Robot Learning in Homes – Improving Generalization and Reducing Dataset Bias
Abstract: Data-driven approaches to solving robotic tasks have gained a lot of traction in recent years. However, most existing policies are trained on large-scale datasets collected in curated lab settings. If we aim to deploy these models in unstructured visual environments like people’s homes, they will be unable to cope with the mismatch in data [...]
1 event,
VASC Seminar
Yong Jae Lee
Computer Science Department, University of California, Davis
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 [...]
2 events,
RI Seminar
Bertram F. Malle
Department of Cognitive, Linguistic & Psychological Sciences and Humanity-Centered Robotics Initiative , Brown University
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 [...]
RI Seminar
Claire J. Tomlin
Electrical Engineering & Computer Sciences, UC Berkeley
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 [...]
1 event,
PhD Speaking Qualifier
Fahad Islam
Online, Interactive User Guidance for High-dimensional, Constrained Motion Planning
Abstract: We consider the problem of planning a collision-free path for a high-dimensional robot. Specifically, we suggest a planning framework where a motion-planning algorithm can obtain guidance from a user. In contrast to existing approaches that try to speed up planning by incorporating experiences or demonstrations ahead of planning, we suggest to seek user guidance [...]
1 event,
Faculty Events
RI Faculty Social
RI Faculty Social
All Robotics Institute faculty are invited to attend this informal team-building business/social event. Beverages and snacks will be provided.
1 event,
PhD Thesis Proposal
Kumar Shaurya Shankar
MRFMaps: A Representation for Multi-Hypothesis Dense Volumetric SLAM
Abstract: Robust robotic flight requires tightly coupled perception and control. Conventional approaches employ a SLAM algorithm to infer the most likely trajectory and then generate an occupancy grid map using dense sensor data for planning purposes. In such approaches all the robustness and accuracy costs are offset to the SLAM algorithm; if there are any […]
2 events,
PhD Thesis Defense
Akshara Rai
Learning to learn from simulation: Using simulations to learn faster on robots
Abstract: Learning for control is capable of acquiring controllers in novel task scenarios, paving the path to autonomous robots. However, typical learning approaches can be prohibitively expensive in terms of robot experiments, and policies learned in simulation do not transfer directly due to modelling inaccuracies. This encourages learning information from simulation that has a higher […]
RI Seminar
Hanumant Singh
Mechanical & industrial Engineering, Northeastern University
Bipolar Robotics – From the Arctic to the Antarctic with a stop for Fisheries in the middle latitudes.
Abstract: The Arctic, Antarctic and Greenland remain some of the least explored parts of the planet. This talk looks at efforts over the last decade to explore areas under-ice which have traditionally been difficult to access. The focus of the talk will be on the robots, the role of communications over low bandwidth acoustic links, […]
Carnegie Mellon University
Carnegie Mellon University
Carnegie Mellon University
Carnegie Mellon University