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Sanjay Jayalakshmi Prabakar
Mid-level Robotics Engineer specializing in surgical robotics, teleoperation, and reinforcement learning
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About
Robotics software engineer with hands-on experience across reinforcement learning and ROS/ROS2, including a project teaching Boston Dynamics Spot to open a door by combining vision-based pose estimation with SAC-trained IK and a walking policy in MuJoCo. Previously built ROS Noetic control for surgical robots using RCM with MoveIt IK and achieved sub-0.02s latency via threading; also participated in a NASA ROS2 space simulation building rover teleop and sensor-driven mapping.
Experience
Education
Key Strengths
- Integrated multiple learned sub-policies (walking + IK + vision) into a unified control system for Spot door-opening
- Debugged real-time simulator control issues by tuning fixed step rates to match physical dynamics
- Reduced surgical robot control latency to <0.02s using refactoring into classes, ROS subscribers, and threading
- Strong simulation-first workflow (debugging in simulator before deploying to real robots)
- Hands-on ROS/ROS2 integration across manipulators and mobile robots (MoveIt, URDF, Gazebo, sensors)
- Practical experience networking heterogeneous robots across multiple laptops; mitigated latency by switching from WiFi to wired
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