RI Seminar
Bertram F. Malle
Professor
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

Newell-Simon Hall 3305

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
Professor
Electrical Engineering & Computer Sciences, UC Berkeley

Safe Learning in Robotics

1305 Newell Simon Hall

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 [...]

PhD Speaking Qualifier
Robotics Institute,
Carnegie Mellon University

Online, Interactive User Guidance for High-dimensional, Constrained Motion Planning

GHC 8102

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 [...]

Faculty Events

RI Faculty Social

Tazza D'Oro, 3rd floor, Gates and Hillman Centers

All Robotics Institute faculty are invited to attend this informal team-building business/social event. Beverages and snacks will be provided.

PhD Thesis Proposal
Robotics Institute,
Carnegie Mellon University

MRFMaps: A Representation for Multi-Hypothesis Dense Volumetric SLAM

GHC 4405

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 [...]

PhD Thesis Defense
Robotics Institute,
Carnegie Mellon University

Learning to learn from simulation: Using simulations to learn faster on robots

NSH 4305

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 [...]