Shantani Sinha

About Shantani Sinha

As a graduate student researcher at the Dynamic Robot Autonomy Interaction and Locomotion Laboratory, I am passionate about developing innovative solutions for humanoid robotics, especially in the context of uneven terrains. I’m excited to share that I have successfully completed my master’s thesis titled “A Supervisory Control Approach for Digit Navigation on Inclined Terrain” under the supervision of Prof. Ioannis Poulakakis. The project focuses on development and implementation of a Supervisory Control System capable of operating in the presence of potentially large parametric uncertainties, specifically addressing the varying inclination angles of the terrain. We demonstrated the effectiveness of our method by applying it to the bipedal robot Digit, enabling it to walk on inclined terrain.I have a strong background in electrical and electronics engineering, with two years of experience at Solinas Integrity Pvt Ltd, a technology-based startup located in the IIT Madras Research Park. There, I contributed to the design and development of three versions of Endobot, a water pipeline inspection robot, and iGlobus, a self-propelled leak detection robot for the oil and gas sector. I also have certifications and publications in robotics and mechatronics, demonstrating my skills in Arduino IDE, motion planning, and hardware design. I am eager to apply my knowledge and expertise to address real-world challenges and advance the field of robotics.

Experience

1. Robotics Controls Engineer

   General Motors

   Jan 2025 — Present · US

   Developed and deployed Autonomous Mobile Robots (AMRs) with full mechanical, electrical, and software integration.• Calibrated and integrated cameras and LiDAR for accurate perception, navigation, and obstacle avoidance.• Implemented motor control, safety systems, and industrial communication for reliable autonomous operation.• Used Python and ROS 2 for simulation, motion planning, and real-world robot deployment.• Calibrated and integrated cameras within NVIDIA Isaac Manipulator for accurate perception, object detection, and safe motion planning of a 6-DOF UR10e collaborative robot.• Developed motion planning and collision avoidance for a 6-DOF UR10e cobot using NVIDIA Isaac Manipulator, deploying solutions from simulation to hardware.

Education

• University of Delaware

  Master's degree, Mechatronics, Robotics, and Automation Engineering

• University of Delaware

  Master of Science with thesis - MS, Mechatronics, Robotics, and Automation Engineering

• Madan Mohan Malaviya University of Technology

  Bachelor of Technology - BTech, Electrical Engineering