30 citations · 62 across the 11 of their papers we have counts for
5 papers · 1 filter
Robot-Supervised Learning for Object Segmentation
Victoria Florence, Jason J. Corso, Brent Griffin
To be effective in unstructured and changing environments, robots must learn to recognize new objects. Deep learning has enabled rapid progress for object detection and segmentatio…
Video Object Segmentation-based Visual Servo Control and Object Depth Estimation on a Mobile Robot
Brent A. Griffin, Victoria Florence, Jason J. Corso
To be useful in everyday environments, robots must be able to identify and locate real-world objects. In recent years, video object segmentation has made significant progress on de…
Kinematically-Informed Interactive Perception: Robot-Generated 3D Models for Classification
Abhishek Venkataraman, Brent Griffin, Jason J. Corso
To be useful in everyday environments, robots must be able to observe and learn about objects. Recent datasets enable progress for classifying data into known object categories; ho…
A Critical Investigation of Deep Reinforcement Learning for Navigation
Vikas Dhiman, Shurjo Banerjee, Brent Griffin +2
The navigation problem is classically approached in two steps: an exploration step, where map-information about the environment is gathered; and an exploitation step, where this in…
Predicting Future Lane Changes of Other Highway Vehicles using RNN-based Deep Models
Sajan Patel, Brent Griffin, Kristofer Kusano +1
In the event of sensor failure, autonomous vehicles need to safely execute emergency maneuvers while avoiding other vehicles on the road. To accomplish this, the sensor-failed vehi…