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Ran Wang passes his Ph.D. defense!
Lab member Kartik successfully defends his Master’s thesis!
Congratulations to lab member Kartik Prakash on successfully defending his Master’s thesis titled ‘Towards Development of a Novel Structurally Aided Long-Term Odometry and Deployment of Precision Navigation Tasks for Warehouse Applications’. Kartik will be joining Vecna Robotics as a Robotics Engineer.
Lab member Karthikeya successfully defends his Master’s thesis!
Congratulations to lab member Karthikeya Parunandi on successfully defending his master’s thesis. Karthikeya’s thesis was on ‘Perturbation Feedback Approaches in Stochastic Optimal Control: Applications to Model-based and Model-free Problems in Robotics’.
Paper on T-PFC is accepted to RA-L and IROS-2019!
Our paper “T-PFC: A Trajectory-Optimized Perturbation Feedback Control Approach” has been accepted for publication in Robotics and Automation Letters (RA-L) and also for presentation at IROS-2019, which will be held at Macau, China.
Karthikeya presents work on SLAM at ICRA ’19!
Lab member Karthikeya presents work on “Robust Pose-Graph SLAM Using Absolute Orientation Sensing” (published in IEEE Robotics and Automation Letters, vol. 4, no. 2, pp. 981-988) at ICRA 2019 held at Montreal, Canada. Link to the poster: link
Lab member Dilshad Raihan successfully defends his Ph.D.!
Congratulations to EDP lab member Dilshad Raihan on successfully defending his Ph.D. Dilshad’s thesis was on ‘Particle Gaussian mixture filters for general nonlinear non-Gaussian Bayesian estimation’. He will be employed as a Data scientist at Anadarko Petroleum Corporation.
Lab member Saurav Agarwal successfully defends his Ph.D.!
Our heartiest congratulations to EDP Lab member Saurav Agarwal who successfully defended his Ph.D. on Dec 6, 2017. Saurav will be working full-time on a warehouse automation startup after his Ph.D.
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.