Field Robotics Center Seminar
Robotics Institute,
Carnegie Mellon University

Belief Space Planning for Reducing Terrain Relative Localization Uncertainty in Noisy Elevation Maps

GHC 4405

Abstract Accurate global localization is essential for planetary rovers to reach science goals and mitigate mission risk. Planetary robots cannot currently use GPS or infrastructure for navigating, and hence rely on terrain for determining global position. Terrain relative navigation (TRN) compares planetary rover-perspective images and 3D models to existing satellite orbital imagery and digital elevation [...]

Special Events

Robotics Institute Winter Party

All RI faculty, staff, students and visitors are invited to the Robotics Institute Winter Party!

VASC Seminar
Zach Pezzementi
Lead Robotics Engineer
Carnegie Mellon University / NREC

Comparing apples and oranges: Off-road pedestrian detection on the NREC agricultural person-detection dataset

GHC 6501

Abstract: Person detection from vehicles has made rapid progress recently with the advent of multiple high-quality datasets of urban and highway driving, yet no large-scale benchmark has been available for the same problem in off-road or agricultural environments. In this talk, we present the NREC Agricultural Person-Detection Dataset to spur research in these environments. It [...]

PhD Thesis Proposal
Robotics Institute,
Carnegie Mellon University

Computational Design Tools for Accessible Robotics

Newell-Simon Hall 1305

Abstract: A grand vision in robotics is that of a future wherein robots are integrated in daily human life just as smart phones are today. Such pervasive integration of robots would greatly benefit from faster design and manufacturing of robots that cater to individual needs. However, robots of today often take years to be created [...]

PhD Speaking Qualifier
Robotics Institute,
Carnegie Mellon University

Predictive Corrective Networks for Action Detection

GHC 4303

Abstract: Although computer vision has seen significant advances in static image analysis, the relatively slow advances in video tasks such as action detection suggest we're struggling to build effective temporal models. In this talk, I will present a few main ideas that drive contemporary approaches, such as "two-stream networks" and "3D" convolutional networks. I'll also [...]

VASC Seminar
Debadeepta Dey
Researcher
Microsoft Research AI (MSR AI)

Adaptive Information Gathering via Imitation Learning

GHC 6501

Abstract: In the adaptive information gathering problem, a robot is required to select an informative sensing location using the history of measurements acquired thus far. While there is an extensive amount of prior work investigating effective practical approximations using variants of Shannon’s entropy, the efficacy of such policies heavily depends on the geometric distribution of [...]

RI Seminar
Greg Mori
Professor
School of Computer Science, Simon Fraser University

Deep Structured Models for Human Activity Recognition

1305 Newell Simon Hall

Abstract: Visual recognition involves reasoning about structured relations at multiple levels of detail.  For example, human behaviour analysis requires a comprehensive labeling covering individual low-level actions to pair-wise interactions through to high-level events.  Scene understanding can benefit from considering labels and their inter-relations.  In this talk I will present recent work by our group building [...]