Key Responsibilities
Develop and optimize core robotic algorithms: including motion planning, navigation control, and perception fusion (e.g., SLAM, sensor fusion for LiDAR/vision/IMU). Implement kinematic/dynamic modeling: such as trajectory generation, force control, and enhancing algorithm robustness in dynamic environments. Algorithm integration and testing: integrate algorithms with hardware systems, perform simulation (e.g., using ROS, Gazebo, MuJoCo), and deploy/debug on physical robots. Explore advanced technologies: research cutting-edge approaches such as imitation learning, reinforcement learning, and multimodal models to improve robotic autonomy and decision-making.
Qualifications
Education: Bachelor’s, Master’s, or Ph.D. degree in Robotics, Computer Science, Automation, or related fields. Programming skills: Proficiency in C++/Python, with experience using ROS, OpenCV, and PyTorch/TensorFlow. Theoretical foundation: Solid knowledge of robotics theory (kinematics, control systems, optimization) and sensor processing (LiDAR, vision, IMU). Practical experience: Hands-on experience in motion control, SLAM, or path planning; familiarity with reinforcement learning frameworks is a plus. Comprehensive abilities: Strong problem-solving skills, teamwork spirit, and ability to drive projects from research to deployment.
Preferred Skills
Publications in top conferences (e.g., RSS, CoRL, ICRA, IROS, NeurIPS), or practical experience in multi-robot systems/human-robot collaboration. Experience in training/deploying large-scale AI models in robotics.
INTERN
intern
5/4/2026
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