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Lab member Mohammadhussein Rafieisakhaei successfully defends Ph.D.!
Our heartiest congratulations to lab member Mohammadhussein Rafieisakhaei for successfully defending his Ph.D. Mohammad’s work focused on motion planning under uncertainty, particularly optimization-based methods. He will continue his research at TAMU.
EDP Lab Wins National Innovation Award @ TCW 2017
Saurav Agarwal and Suman Chakravorty, members of the EDP Lab won the 2017 TechConnect National Innovation Award for the newly developed technology “A Method for Highly Accurate Long-Term Localization and Navigation Using On-Board Sensors.” This innovation allows a system, such as a vehicle or robot, to navigate autonomously in previously unknown environments with less than a […]
Paper on RFM-SLAM is Accepted to ICRA 2017
Our paper on a novel technique (RFM-SLAM) for 2D feature based SLAM has been accepted to ICRA 2017 to be held in Singapore!
EDPLab Develops a Novel Technique For Feature-Based SLAM
The SLAM problem is known to have a special property that when robot orientation is known, estimating the history of robot poses and feature locations can be posed as a standard linear least squares problem. We have developed a SLAM framework that uses relative feature-to-feature measurements to exploit this structural property of SLAM. Relative feature […]
Dan Yu Successfully Defends Her Ph.D.!
Our heartiest congratulations to Dr. Yu on successfully defending! Dr. Yu’s research focused on model order reduction techniques for large scale systems, you may find her publications here. Dr. Yu will continue her research at the EDP Lab.
Decentralized State Estimation via a Hybrid of Consensus and Covariance intersection – Technical Report
This paper presents a new recursive information consensus filter for decentralized dynamic-state estimation. No structure is assumed about the topology of the network and local estimators are assumed to have access only to local information. The network need not be connected at all times. Consensus over priors which might become correlated is performed through Covariance Intersection (CI) and consensus over new […]
Saurav Awarded 2015 Roberto Padovani Scholarship From Qualcomm
Lab Member Saurav Agarwal has been selected as one of the winners of the 2015 Roberto Padovani Scholarship for being one of the best performing interns at Qualcomm. The Roberto Padovani Scholarship was created in 2008 to recognize Qualcomm’s corporate research and development interns who demonstrate technical superiority during summer internships. The scholarship is named for Roberto Padovani, […]
Lab member Saurav Agarwal will be at Qualcomm Research
Lab member Saurav Agarwal will be interning at Qualcomm Research in San Diego for the summer and fall of 2015 where he will work on autonomous vision-based navigation for micro aerial vehicles.
Feedback-based Information RoadMaps with Open Motion Planning Library
We are pleased to announce that the developers of OMPL (Open Motion Planning Library) at Rice University have posted a guest article by our lab on our latest work on integrating FIRM with OMPL. We would particularly like to acknowledge the support of Mark Moll in this process. Feel free to browse our code on […]