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Aspiring Robotics Engineer
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Aspiring Robotics Engineer

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N-Raghav/README.md

Hi, I'm Raghav Nallaperumal

MS Robotics Engineering @ WPI (4.0 GPA) | Perception • Control • Manipulation

📧 raghavnallaperumal753@gmail.com
🌐 Portfolio | LinkedIn

I work on perception and control for physical robots. Most recently, I built the grasping pipeline for a Franka Panda at WPI's MER Lab, and I'm currently exploring drone perception and control using a Crazyflie.


Tech stack

Languages: Python, C++, MATLAB
Robotics: ROS 2 (Humble), MoveIt 2, Gazebo, PyBullet
Control: LQR, PID, MPC, Jacobian-based control, trajectory optimization
Perception: OpenCV, PyTorch, SLAM, VIO, camera calibration
Hardware: Franka Emika Panda, Intel RealSense D435, Crazyflie 2.0, Beckhoff TwinCAT PLC


Pinned Loading

  1. Mono-Sense Mono-Sense Public

    Tesla-inspired autonomous driving visualization using monocular camera perception — lane detection, 3D object placement, pedestrian pose estimation, and depth-based scene reconstruction rendered in…

    Jupyter Notebook

  2. Drone-Control-Methods Drone-Control-Methods Public

    Crazyflie 2.0 flight controller (PD/LQR) with polynomial trajectory generation and hardware validation

    Python 1

  3. Deep-Homography-Estimation Deep-Homography-Estimation Public

    Panoroma stiching using homography estimated by classical and deep learning based methods

    Python

  4. SfM-and-NeRF SfM-and-NeRF Public

    Forked from prithvi-raj-b/CV-SfM-and-NeRF

    3-D reconstruction using images by implementing Structure from Motion and Neural Radiance Fields

    Python

  5. Hybrid-Push-Dynamics-Learning-Methods Hybrid-Push-Dynamics-Learning-Methods Public

    A comparative implementation and analysis of physics-based, neural network, and hybrid models for predicting object motion in robotic pushing tasks.

    Python

  6. Reinforcement-Learning-for-Picking-Task Reinforcement-Learning-for-Picking-Task Public

    Python