Experience

roahmlab

UAV Navigation with PX4 Autopilot and QGroundControl

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Experience Overview:

  • Autopilot Configuration: Configured PX4 Autopilot on Ubuntu 22.04 using Docker container deployment.
  • Ground Control Integration: Integrated QGroundControl with the local machine, establishing a connection via a designated port.
  • UAV Testing: Conducted testing with tailsitter and CRC custom UAVs.
  • Mission Planning and Execution: Developed custom mission plans and managed execution phases including takeoff, navigation, and landing.
  • Position Control and Precision Navigation: Implemented position control algorithms and ensured precise waypoint navigation.
  • Tools Used:
    • C++
    PX4-Autopilot
    ROS
    PX4-Autopilot
    Gazebo

    Trajectory Planning and Optimization for Robotic Navigation

    Robotic Navigation Project Image

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    Experience Overview:

  • Interface Development: Enhanced REFINE controller interfaces for improved system interaction.
  • FRS Generation and Management: Developed Forward Reachable Sets (FRS) and implemented FRS_loader and FRS_Instance for efficient management.
  • Objective and Cost Function Implementation: Crafted objective functions and cost calculations for trajectory planning.
  • Planner Development: Created Refine Planner for iterative trajectory planning, integrating dynamic path selection.
  • Trajectory Optimization: Utilized Trajectory_Factory and RtdTrajOpt class for trajectory optimization and cost efficiency analysis.
  • Tools Used:
    • C++
    Matlab
    matplotlib

    Autonomous Navigation and Manipulation for Robotic Systems

    Autonomous Navigation and Manipulation Project Image

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    Experience Overview:

  • Robotic Arm Kinematics: Derived kinematic equations and DH parameters for a 6-DOF robotic arm.
  • Simulation Verification: Conducted simulations to confirm joint angles against manual calculations.
  • Mobile Manipulator Integration: Developed a PyBullet environment with obstacles for path planning.
  • Path Planning Algorithms: Implemented A* for navigation, extended with RRT for object manipulation.
  • Tools Used: Python, PyBullet, NumPy, Eigen.
    • Python
    NumPy
    Pybullet
    PyTorch
    Efficiency Enhancement in Industrial Logistics

    Efficiency Enhancement in Industrial Logistics

    Efficiency Enhancement in Industrial Logistics

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    Experience Overview:

  • CAD Design: Developed CAD models for AC gas cylinder transportation and tilting mechanisms.
  • Automation Solutions: Worked on the design and implementation of Automated Guided Vehicles and 3MU systems.
  • Process Optimization: Utilized Spaghetti diagrams for streamlining workflows and enhancing efficiency.
  • Digital Andon System: Led the team in deploying a digital Andon system for real-time shop floor monitoring.
  • Tools Used: Creo, CAD, 3D Automation Software.