MSR Thesis Defense
PhD Student
Robotics Institute,
Carnegie Mellon University

Failure Is an Option: How the Severity of Robot Errors Affects Human-Robot Interactions

GHC 4405

Abstract: Just as humans are imperfect, even the best of robots will eventually fail at performing a task. The likelihood of failure increases as robots expand their roles in our lives. Although task failure is a common problem in robotics and human-robot interaction (HRI), there has been little research investigating human tolerance to said failures, [...]

PhD Thesis Defense
Robotics Institute,
Carnegie Mellon University

Extensions of the Principal Fiber Bundle Model for Locomoting Robots

NSH 1305

Abstract: Our goal is to establish a rigorous formulation for modeling the locomotion of a broad class of robotic systems. Recent research has identifi ed a number of systems with the structure of a principal fiber bundle. This framework has led to a number of tools for analysis and motion planning applicable to various robotic [...]

Special Events

2018 Robotics Institute Picnic

Vietnam Veteran's Pavilion @ Schenley Park Overlook Drive, Pittsburgh, United States

Attention: This events time was changed. The original time was 3pm to 7pm, the event is now occurring from 2pm to 6pm. If you had exported the event to add it to your calendar, please be sure to update the time in your calendar appropriately. Private Event: By Invitation Only   SOCIALIZE, EAT, DRINK & [...]

RI Seminar
Assistant Professor
Robotics Institute,
Carnegie Mellon University

Imaging the World One Photon at a Time

1305 Newell Simon Hall

Abstract: The heart of a camera and one of the pillars for computer vision is the digital photodetector, a device that forms images by collecting billions of photons traveling through the physical world and into the lens of a camera.  While the photodetectors used by cellphones or professional DSLR cameras are designed to aggregate as [...]

RI Seminar
Principal Systems Scientist / Director, NREC
Robotics Institute,
Carnegie Mellon University

Lesson Learned from Two Decades of Robotics Development and Thoughts on Where We Go from Here

GHC 6115

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 [...]

RI Seminar
Associate Professor
Robotics Institute,
Carnegie Mellon University

Factor Graphs for Robot Perception

1305 Newell Simon Hall

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 [...]

PhD Thesis Proposal
Robotics Institute,
Carnegie Mellon University

Scaling up Self-Supervision for Robot Learning

GHC 8102

Abstract: A general purpose robot will need to interact with objects in cluttered environments with minimal supervision. Machine learning provides methods that can deal with these complex tasks without explicitly modelling the environment. More recently, deep learning techniques combined with large scale data has revolutionized the fields of computer vision, language processing and reinforcement learning. [...]

VASC Seminar
Emily Denton
Ph.D. Student
Courant Institute at New York University

Towards better methods of video generation

Gates-Hillman 6115

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 [...]