Open Positions



Operating Home Appliances using the Baxter Robot

Description: Grasping is a fundamental problem which need to be solved by humanoid robots or robotic arms. Grasping traditionally involves end effector planning coupled with perception and complex controls. In this project, you will be working on operating refrigerator and microwave oven in particular. Check [1] and [2] videos for reference. The codebase is available and you will be responsible for improving the robustness of the system.
Goal: Operating the refrigerator and microwave oven using Baxter.

Contact: Cornelia Fermuller (fer[at]cfar[dot]umd[dot]edu))
Skills Required: Proficiency in ROS, C++, Linux and Python.
Thesis Type: Semester Project/Independent Study
Job Opportunities: Upon successful completion of the project, students will have a good chance of getting a job at Amazon and any other robotic arm companies or robotics automation companies.


Quadrotor Swarm

Description: You will be addressing the problem of motion planning and cooperative control in a multiple quadrotor system. This project entails the problem of cooperative planning to simulate the concurrent assignment and planning task.
Goal: Your task is to implement the following paper on a quadrotor swarm.

Contact: Nitin Sanket (nitinsan[at]terpmail[dot]umd[dot]edu) and Chahat Deep Singh (chahat[at]terpmail[dot]umd[dot]edu)
Skills Required: Linux, C/C++, Python and ROS.
Thesis Type: Semester Project/Independent Study
Job Opportunities: Upon successful completion of the project, students will have a good chance of getting a job at DJI and Parrot.


Following a known Aggressive trajectory on a quadrotor with on-board sensing

Description: Quadrotors are very agile vehicles and their agility shines through when executing high speed trajectories. This has been done using motion capture system which gives “perfect” estimates of the position and orientation of the quadrotor. Executing these high speed trajectories using on-board sensing is impressive and very useful for various tasks like drone racing, obstacle avoidance and flying through narrow gaps.
Goal: Implement aggressive trajectory following using only a monocular camera and an IMU with all processing done on-board.

Contact: Nitin Sanket (nitinsan[at]terpmail[dot]umd[dot]edu) and Chahat Deep Singh (chahat[at]terpmail[dot]umd[dot]edu)
Skills Required: Linux, C/C++, Python and ROS.
Thesis Type: Semester Project/Independent Study
Job Opportunities: Upon successful completion of the project, students will have a good chance of getting a job at DJI and Parrot.



Deep Learning based Robust Grasping of objects using UR-10, Sawyer and Baxter

Description: Grasping is a fundamental problem which need to be solved by humanoid robots or robotic arms. Grasping traditionally involves end effector planning coupled with perception and complex controls.
Goal: Using Deep Learning based models to perform robust grasps. You’ll be using the DexNet 2.0 from UC Berkeley to implement these robot grasps.

Contact: Kanishka Ganguly (kganguly[at]terpmail[dot]umd[dot]edu))
Skills Required: Deep Learning, Linux, Python and ROS.
Thesis Type: Semester Project/Independent Study/Masters Thesis
Job Opportunities: Upon successful completion of the project, students will have a good chance of getting a job at Amazon and any other robotic arm companies or robotics automation companies.


Visual Inertial Odometry using Event Cameras

Description: Event-based camera is a new vision sensor with high temporal resolution, superior sensitivity to light and low latency, which are ideally suited for real-time motion analysis. The camera outputs asynchronous sparse event streams which correspond to the scene illumination changes.
Goal: The goal of the project is to estimate the camera pose by fusing sparse event stream and IMU measurements through traditional filtering/deep learning approaches.

Contact: Chethan Parameshwara (cmparam9[at]terpmail.umd.edu)
Skills Required: C/C++, ROS, Linux.
Thesis Type: Semester Project/Independent Study
Job Opportunities: Upon successful completion of the project, students will have a good chance of getting a job at any AR/Drone/Self-driving car companies.


           

 info[at]prg.cs.umd.edu