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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.


Saurav Agarwal Defense

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 one-meter position error for 100 kilometers of motion without relying on GPS or any pre-built maps. The applications of this technology are immense and include military and commercial use, such as self-driving cars.

The TechConnect National Innovation Award selects the top early-stage innovations from around the world through an industry-review process of the top 20 percent of annually submitted technologies into the TechConnect National Innovation Summit. Rankings are based on the potential positive impact the submitted technology will have on a specific industry sector.

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!

Can a robot drive 100s of Kilometers with < 1 m Error?

A considerably difficult aspect of Simultaneous Localization and Mapping (SLAM) is the problem of uncertainty constrained long term point-to-point navigation where global loop closures to eliminate estimation biases may not be possible. In such scenarios, a prime concern is to control the rate of localization error growth. We have developed fundamental results on the underlying problem of localization and a novel SLAM technique that allows sub-meter localization error for a > 100 km trajectory without loop closure and using only on-board sensors, i.e., no GPS.

Applications may include:

  1. Self-driving cars
  2. Precision farming
  3. Planetary rovers
  4. Unmanned Aerial Vehicles
  5. Autonomous Underwater Vehicles

To license this technology for commercial use or to learn more, please contact lab director Dr. Suman Chakravorty or Dr. Ismail Sheikh (smismail[at]tamu[dot]edu) at Texas A&M University Technology Commercialization, 800 Raymond Stotzer Parkway, Suite 2020, College Station, Texas 77845.