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Yui Chang
Mid-level Robotics Engineer specializing in autonomous navigation, SLAM, and MPC control
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Autonomous marine surface algorithms engineer at CURLY contributing across the full autonomy stack in ROS 2 (C++/Python), from GNSS-IMU InEKF localization (100 Hz) and GTSAM object-level SLAM to semantic mapping and A*/Lie-group MPC planning/control. Strong focus on real-time optimization for constrained embedded hardware, with disciplined debugging/validation using ros2_tracing, rosbag2 replay, and Gazebo, and reproducible deployment via Docker/CI.
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Key Strengths
- Built and integrated end-to-end autonomy stack (mapping, localization, SLAM, planning, control) for autonomous marine surface vehicles
- Implemented GNSS-IMU InEKF localization delivering real-time 100 Hz state estimation
- Integrated GTSAM object-level SLAM with persistent landmarks to mitigate long-term drift/enable loop closure
- Optimized autonomy algorithms for limited onboard compute via C++ and multithreading
- Real-time ROS 2 performance debugging using ros2_tracing, ros2 topic hz/bw, rqt_graph, and rosbag2 replay
- Designed decentralized pub-sub communication for heterogeneous/distributed robots with time synchronization and reliability tuning
- Simulation-to-hardware validation using Gazebo plus reproducible deployment with Docker and CI-style automated builds
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