Frank Dellaert

2014
Roberts, R., and F. Dellaert, "Direct Superpixel Labeling for Mobile Robot Navigation Using Learned General Optical Flow Templates", Intelligent Robots and Systems (IROS), 2014 IEEE/RSJ International Conference on, 2014. PDF icon iros2014.Roberts.Dellaert.final_.pdf (1.62 MB)
Ta, D-N., M. Kobilarov, and F. Dellaert, "A factor graph approach to estimation and model predictive control on Unmanned Aerial Vehicles", Unmanned Aircraft Systems (ICUAS), 2014 International Conference on, May, 2014. PDF icon icuas2014.Ta_.Kobilarov.Dellaert.final_.pdf (666.28 KB)
Kundu, A., Y. Li, F. Dellaert, F. Li, and J. J. M. Rehg, Joint Semantic Segmentation and 3D Reconstruction from Monocular Video, , 2014. PDF icon eccv2014.Kundu_.Li_.Dellaert.Li_.Rehg_.printed.pdf (4.53 MB)
Ta, D-N., and F. Dellaert, "Linear-Time Estimation with Tree Assumed Density Filtering and Low-Rank Approximation", Intelligent Robots and Systems (IROS), 2014 IEEE/RSJ International Conference on, 2014. PDF icon iros2014.Ta_.Dellaert.final_.pdf (985.04 KB)
Ta, D-N., K. Ok, and F. Dellaert, "Vistas and parallel tracking and mapping with Wall–Floor Features: Enabling autonomous flight in man-made environments", Robotics and Autonomous Systems, 2014. PDF icon ras13.Ta_.Ok_.Dellaert.printed.pdf (1.53 MB)
2013
Ta, D-N., K. Ok, and F. Dellaert, "Monocular Parallel Tracking and Mapping with Odometry Fusion for MAV Navigation in Feature-lacking Environments", IEEE/RSJ IROS’13 International Workshop on Vision-based Closed-Loop Control and Navigation of Micro Helicopters in GPS-denied Environments, Tokyo, Japan, 11/2013. PDF icon iros2013.Ta_.Ok_.Dellaert.final_.pdf (627.16 KB)
Roberts, R., and F. Dellaert, "Optical Flow Templates for Superpixel Labeling in Autonomous Robot Navigation", 5th Workshop on Planning, Perception and Navigation for Intelligent Vehicles (PPNIV13), 2013. PDF icon ppniv2013.Roberts.Dellaert.printed.pdf (1.03 MB)
 

Dynamics and Control Systems Lab

 

Robotic Mobility Group

 

Aerospace Robotics and Embedded Systems Laboratory

About us

We are three research groups from Georgia Tech, the Massachusetts Institute of Technology, and the University of Southern California, collaborating to perform basic research on high-speed autonomous driving.  We are most interested in researching biologically-inspired methods in the realms of both perception and control.

Acknowledgment

This work was supported by the Army Research Office under MURI Award W911NF-11-1-0046.