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MSSreejith
Robotics engineer with a strong focus on indoor autonomous navigation, leveraging expertise in SLAM, sensor fusion, and path planning to develop intelligent, self-guided systems.
經歷
Engineered a ROS2-based SLAM solution that enhanced indoor localization precision by 30%, contributing to the development of autonomous features for SK Magic's upcoming products. Spearheaded a comprehensive software debugging initiative, reducing critical system errors and boosting reliability of navigation in varied indoor environments.
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I led the development of indoor SLAM systems for autonomous robotics, utilizing ROS to achieve highly accurate navigation in complex indoor environments. My work involved integrating 2D/3D LiDARs, depth cameras, IMUs, and GPS through advanced sensor fusion techniques to build robust localization pipelines. I managed collaborative robot projects using UR, Panda, and Kinova arms, optimizing motion coordination in ROS for pick-and-place operations powered by object recognition.
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Trained Deep Convolutional Neural Networks( DCNN) models for image and facial recognition using TensorFlow, leveraging big data for enhanced accuracy. Developed a face recognition system for Caffe Robots using TensorFlow, improving customer engagement and service quality.
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Adapted and optimized existing ADAS software, rectifying errors and ensuring compatibility with new hardware, ultimately enhancing system performance.
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學歷
活動
프로젝트
Air Purfier Robot
2024년 5월 - 2025년 4월 · 1년
I developed a ROS2-based SLAM navigation system for an indoor air purifier robot, enabling it to autonomously map and navigate home environments. This solution significantly improved autonomous coverage efficiency and served as a foundation for SK Magic’s next-generation smart home products.
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SLAM
2020년 1월 - 현재 · 6년 1개월
Indoor SLAM using Lidar, IMU and Wheel Odometery. Mapping using Hector SLAM/Cartographer. Navigation and Obstacle avoidance is implemented with good accuracy. It is done using both ROS and ROS2.