San Francisco Bay Area
As a Research Engineer at Collaborative Robotics, I work on developing and integrating localization and mapping algorithms for autonomous systems. I use various SLAM techniques and perform multi-sensor data fusion using Lidar, IMU, and Stereo Vision data. I have a Master of Science in Electrical and Computer Engineering from Northeastern University, where I conducted research on novel control and planning strategies for unmanned systems and robotics. I designed and prototyped a mechanically intelligent flapping wing aerial robot, constructed a Simulink based testing environment with real-time motion capture and multi-axis force and torque sensor, and created a URDF model for a 16 dof Quadruped robot for simulations in Gazebo. I also have experience in kinematic and dynamic system modeling, computer vision, systems engineering and integration, autopilot firmware development, and multi UAV collaborative control. I have published papers in AIAA, ACM, and ICC conferences, and received awards for best technical journal paper and overall performance in aero design challenges. I am passionate about developing better robotic platforms that can navigate and perform in urban environments and become a part of our daily lives. I am always eager to learn new skills and technologies, and to collaborate with other researchers and professionals in the field of robotics. Feel free to reach out to me to know more about my past projects and experiences, or to have any discussion related to robotics in general!
Leading the development of a multi-modal (Lidar, IMU, Camera) Simultaneous Localization and Mapping solution for indoor GPS-denied dynamic environments, with long term re-localization capabilities. Spearheaded sensor selection and system design for the above-mentioned SLAM solution, emphasizing accuracy and cost-efficiency. Leading testing efforts and integration with autonomy stack, ensuring seamless functionality within broader navigation systems.
• Conceptualized and deployed a visual positioning system for localization to aid all development in Autonomy department, saving approximately USD 60,000 in development costs (alternative to systems like VICON). • Led the development and testing of an in-house SLAM solution using IMU and Lidars for indoor environment, integrated the localization data with WMS and implemented optimal path planning using A* based planner. • Developed assisted-driving features (automatic lane centering, cruise control and pallet docking) for tele-operated forklifts resulting in a 25% increase in operator efficiency.
• Implemented various SLAM techniques (LOAM, LeGO-LOAM, OrbSLAM) with factor graph based optimization for Loop Closures using Lidar, IMU, and Stereo Vision data. • Designed and developed a waterproof visual-inertial odometry system for use in autonomous underwater robotics applications and field tested it with an AUV. • Performed multi-sensor data fusion using Optical Flow, Lidar, IMU, and GPS for better localization of an autonomous multi-rotor platform.
• Designed and prototyped a mechanically intelligent flapping wing aerial robot for testing novel active stabilization techniques; created an Arduino based micro autopilot with onboard IMU and remote control with power distribution PCB. • Constructed a Simulink based testing environment with real-time motion capture (using Opti-track), RTOS STM32 based actuation and multi-axis force and torque sensor for automated system identification of aerial robots. • Created a URDF model for 16 dof Quadruped robot for simulations in Gazebo, implemented low level PID controller for tracking gait trajectories.