Responsible for the system dynamics modeling of AI smart tower cranes, analyzing their actuation, friction, payload, and external disturbance characteristics, and developing simplified models for control and motion planning algorithm design.
Build and maintain high-fidelity robotics simulation environments (Gazebo/Unity/Simulink) to enable full-chain testing of controllers and planners.
Lead the development, validation, and maintenance of control and motion planning algorithms for smart tower cranes, including but not limited to Model Predictive Control (MPC), robust control, adaptive control, and Reinforcement Learning (RL) based intelligent controllers.
Migrate and deploy simulation-verified algorithms into the product ROS (1/2) C++ software framework, ensuring real-time performance, reliability, and integration with hardware systems.
Manage Docker image creation, environment containerization, and deployment for algorithm modules, ensuring consistency between R&D and delivery environments, and maintain code/experiment reproducibility via CI/CD pipelines.
Author and maintain technical documentation, including model assumptions, interface definitions, test reports, and algorithm white papers, providing theoretical support and engineering guidance to the team.
Qualifications:
Must hold a Master or Ph.D. degree in Robotics, Automation, Mechatronics, or a closely related field.
Possess a solid foundation in dynamics modeling and modern control theory, with the ability to independently conduct model simplification, analysis, and controller design for complex systems.
Proficient in using Python/Matlab-Simulink for dynamics modeling, control algorithm prototyping, and simulation analysis.
Have hands-on experience in building, model integration, and closed-loop simulation testing within robotics simulation environments (e.g., Gazebo, Unity).
Proficient in C++ development within the ROS framework on Linux, capable of efficiently and stably implementing algorithms as integrable ROS nodes.
Familiar with the routine development and deployment workflow using Docker, and able to manage dependencies and environments using containerization technology.
Possess excellent analytical, problem-solving, teamwork, and communication skills.
Experience in deploying and debugging robotic systems in real construction sites, outdoor, or highly perturbed environments.
Familiar with industrial communication protocols such as Modbus and CAN, with experience in software-hardware integration and debugging.
Proficient in Cantonese, Mandarin, and English, with strong communication skills.
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Build and maintain high-fidelity robotics simulation environments (Gazebo/Unity/Simulink) to enable full-chain testing of controllers and planners.
Lead the development, validation, and maintenance of control and motion planning algorithms for smart tower cranes, including but not limited to Model Predictive Control (MPC), robust control, adaptive control, and Reinforcement Learning (RL) based intelligent controllers.
Migrate and deploy simulation-verified algorithms into the product ROS (1/2) C++ software framework, ensuring real-time performance, reliability, and integration with hardware systems.
Manage Docker image creation, environment containerization, and deployment for algorithm modules, ensuring consistency between R&D and delivery environments, and maintain code/experiment reproducibility via CI/CD pipelines.
Author and maintain technical documentation, including model assumptions, interface definitions, test reports, and algorithm white papers, providing theoretical support and engineering guidance to the team.
Qualifications:
Must hold a Master or Ph.D. degree in Robotics, Automation, Mechatronics, or a closely related field.
Possess a solid foundation in dynamics modeling and modern control theory, with the ability to independently conduct model simplification, analysis, and controller design for complex systems.
Proficient in using Python/Matlab-Simulink for dynamics modeling, control algorithm prototyping, and simulation analysis.
Have hands-on experience in building, model integration, and closed-loop simulation testing within robotics simulation environments (e.g., Gazebo, Unity).
Proficient in C++ development within the ROS framework on Linux, capable of efficiently and stably implementing algorithms as integrable ROS nodes.
Familiar with the routine development and deployment workflow using Docker, and able to manage dependencies and environments using containerization technology.
Possess excellent analytical, problem-solving, teamwork, and communication skills.
Experience in deploying and debugging robotic systems in real construction sites, outdoor, or highly perturbed environments.
Familiar with industrial communication protocols such as Modbus and CAN, with experience in software-hardware integration and debugging.
Proficient in Cantonese, Mandarin, and English, with strong communication skills.
#J-18808-Ljbffr
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