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Rupesh Pathak
Junior Data Scientist and Robotics Perception Engineer specializing in GenAI and autonomous systems
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About
Robotics software architect who built an automated pick-and-place palletizing prototype at BLACK-I-ROBOTICS, spanning perception (multi-RealSense fusion, segmentation, 6D pose, ICP), GPU-accelerated motion planning (MoveIt 2 + NVIDIA CuRobo), grasp generation, and safety (human detection + safe mode). Also brings cloud/CI/CD depth from VERIDIX AI (AWS Cognito/Lambda/ECS and CodePipeline stack) and demonstrated strong debugging chops by reducing outdoor rover EKF drift to ~5 cm via Allan variance-based IMU tuning.
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Key Strengths
- End-to-end robotics system architecture from concept to client prototype
- Advanced perception stack: segmentation + 6D pose + ICP with multi-RealSense super point cloud
- GPU-accelerated motion planning integration (MoveIt 2 + NVIDIA CuRobo) to reduce planning latency
- Strong ROS 2 engineering: custom nodes/packages, Actions/Services, TF/URDF, QoS tuning for heterogeneous data
- Constraint-aware grasp planning integrated directly into MoveIt (moveit_msgs/Grasp)
- Real-time optimization via profiling, environment model simplification, and collision-parameter tuning
- Safety-focused robotics: human detection triggering safe-mode velocity/acceleration scaling
- Debugging state estimation drift using Allan variance and EKF covariance tuning (achieved ~5 cm pose error)
- Simulation-to-real workflow using Gazebo/Isaac Sim and containerized deployments with Docker
- Cloud/CI/CD experience on AWS (Cognito/Lambda/ECS + CodeBuild/CodePipeline/CodeCommit)
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