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Ronit Shetty
Entry-level Robotics Engineer specializing in SLAM, sensor fusion, and embedded avionics
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About
Robotics software engineer focused on perception/SLAM and systems integration, recently built a quasi-dynamic mapping pipeline to track and reconstruct articulated objects (e.g., drawers) from RGB video using SAM2, COLMAP SfM, and 3D Gaussian Splatting. Also has strong ROS2 sensor-pipeline experience (custom messages, MCAP rosbag deserialization, tf2) and demonstrated real-time performance tuning by accelerating an ICP-based LiDAR SLAM component ~30x (from ~3s to <100ms per frame).
Experience
Education
Key Strengths
- End-to-end integration of deep learning and classical CV pipelines (SAM2 + COLMAP + 3D Gaussian Splatting)
- Bridging incompatible I/O formats and building conversion layers across frameworks
- Strong grasp of coordinate frames and camera intrinsics/extrinsics to maintain spatial consistency
- ROS 2 development in both Python and C++ (custom drivers, packages, and message types)
- Real-time SLAM optimization: improved ICP runtime from ~3s to <100ms per frame (~30x) using KD-trees and adaptive termination
- Reproducible robotics environments with Docker (CUDA/ROS2/toolchains) and CI automation (GitLab CI/GitHub Actions)
- Simulation-first validation using Gazebo for sensor pipelines prior to hardware deployment
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