RI Seminar
Hanumant Singh
Professor
Mechanical & industrial Engineering, Northeastern University

Bipolar Robotics – From the Arctic to the Antarctic with a stop for Fisheries in the middle latitudes.

1305 Newell Simon Hall

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, [...]

VASC Seminar
Philipp Krähenbühl
Professor
Computer Science Department, University of Texas at Austin

Video Compression for Recognition & Video Recognition for Compression

GHC 6501

Abstract: Training robust deep video representations has proven to be much more challenging than learning deep image representations. One reason is: videos are huge and highly redundant. The 'true' and interesting signal often drowns in too much irrelevant data. In the first part of the talk, I will show how to train a deep network [...]

Faculty Candidate
Assistant Research Professor
Robotics Institute,
Carnegie Mellon University

Multimodal Computational Behavior Understanding

Emotions influence our lives. Observational methods of measuring affective behavior have yielded critical insights, but a persistent barrier to their wide application is that they are labor-intensive to learn and to use. An automated system that can quantify and synthesize human affective behavior in real-world environments would be a transformational tool for research and for [...]

RI Seminar
Associate Professor
Robotics Institute,
Carnegie Mellon University

Learning Robot Manipulation Skills through Experience and Generalization

1305 Newell Simon Hall

Abstract: In the future, robots could be used to take care of the elderly, perform household chores, and assist in hazardous situations. However, such applications require robots to manipulate objects in unstructured and everyday environments. Hence, in order to perform a wide range of tasks, robots will need to learn manipulation skills that generalize between [...]

Special Talk
Dr. Yan Ke
founder and CTO of
Colbotics

Fully Autonomous Drones for Wind Power Turbine Inspection

3305 Newell-Simon Hall

Abstract: The wind energy industry is growing rapidly. In the U.S. alone, the wind industry invested more than $11 billion in new plants in 2017 and added more than 7,000 megawatts of new capacity, representing 25% of all electric capacity added. One of the biggest challenges to growth remains the high costs of constructing wind [...]

RI Seminar
George Konidaris
Assistant Professor
Department of Computer Science, Brown University

Signal to Symbol (via Skills)

1305 Newell Simon Hall

Abstract: While recent years have seen dramatic progress in the development of affordable, general-purpose robot hardware, the capabilities of that hardware far exceed our ability to write software to adequately control. The key challenge here is one of abstraction: generally capable behavior requires high-level reasoning and planning, but perception and actuation must ultimately be performed [...]

PhD Thesis Proposal
Robotics Institute,
Carnegie Mellon University

Sparse and Dense Methods for Underwater Localization and Mapping with Imaging Sonar

GHC 4405

Abstract: Imaging sonars have been used for a variety of tasks geared towards increasing autonomy of underwater vehicles: image registration and mosaicing, vehicle localization, object recognition, mapping, and path planning, to name a few. However, the complexity of the image formation has led many algorithms to make the restrictive assumption that the scene geometry is [...]

PhD Thesis Proposal
Robotics Institute,
Carnegie Mellon University

Deep Interpretable Non-rigid Structure from Motion

GHC 4405

Abstract: Current non-rigid structure from motion (NRSfM) algorithms are limited with respect to: (i) the number of images, and (ii) the type of shape variability they can handle. This has hampered the practical utility of NRSfM for many applications within vision. Deep Neural Networks (DNNs) are an obvious candidate to help with such issue. However, [...]