PhD Speaking Qualifier
Robotics Institute,
Carnegie Mellon University

Expressive Real-time Intersection Scheduling

Newell Simon Hall 1507

Abstract: Traffic congestion is a major annoyance throughout global metropolitan areas. This talk will present Expressive Real-time Intersection Scheduling (ERIS), a schedule-driven control strategy for adaptive intersection control to reduce traffic congestion. ERIS maintains separate estimates for each lane approaching a traffic intersection allowing it to more accurately estimate the effects of scheduling decisions than [...]

PhD Speaking Qualifier
Robotics Institute,
Carnegie Mellon University

Scaling up Self Supervised Robot Learning

Newell Simon Hall 1507

Abstract Robot learning holds promise in alleviating several real world problems, by performing complex behaviors in complex environments. But what is the right way to train these robots? Our methods on self supervision shows encouraging results on several tasks like grasping objects, pushing objects and even flying drones. One key challenge with these methods is [...]

PhD Speaking Qualifier
Robotics Institute,
Carnegie Mellon University

Data Collection for Screwdriving

Gates Hillman Center 4405

Abstract: As the use of robotic manipulation in manufacturing continues to increase, the robustness requirements for fastening operations such as screwdriving increase as well. To investigate the reliability of screwdriving and the diverse failure categories that can arise, we collected a dataset of screwdriving operations and manually classified them into stages and result categories. I [...]

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 [...]

PhD Speaking Qualifier

Characterization of Anchoring in Granular Soils

GHC 8102

Abstract: I will present the results of tests conducted to characterize the pullout force of an anchor buried in cohesionless soils. Sensitivity analyses were conducted to understand how key measures of fin geometry affect an anchor's pullout force. To generalize the data collected, I propose a dimensionless model for predicting the performance of arbitrary fin [...]