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Swarnabha Roy
Mid-level Robotics & Computer Vision Engineer specializing in autonomous systems and edge AI
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Robotics/perception researcher (MVOS Lab, South Dakota State University) who built an end-to-end multimodal RGB-D + LiDAR pipeline for autonomous greenhouse harvesting and 3D plant phenotyping. Demonstrated strong production ownership by diagnosing motion blur with ROS-bag + OpenCV metrics and shipping an edge-deployed, scan-quality-aware workflow that boosted barcode read rate to 98% and supported ~70% autonomous pepper detection/harvesting accuracy.
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Key Strengths
- Designed end-to-end multimodal perception system for autonomous greenhouse harvesting (RealSense RGB-D + LiDAR)
- Built robust calibration/registration + URDF-aware collision-aware 3D reconstruction for precise manipulation
- Established rigorous validation protocol vs manual ground truth; achieved MSE ~0.004 and Pearson correlation up to 0.91 on phenotyping traits
- Improved autonomous pepper detection/harvesting performance to ~70% accuracy
- Owned production perception reliability: diagnosed motion-blur root cause and raised barcode read rate to 98% by integrating nav + perception stop-and-scan logic
- Created blur diagnostics using ROS bags + Python/OpenCV (Laplacian variance) and implemented real-time scan-quality gating on Jetson edge
- Engineered real-time camera acquisition architecture (producer-consumer, bounded queue) with stable ~35ms latency and reduced dropped frames to <0.5%
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7 publications
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