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The project aims to develop robust, intelligent and efficient navigation systems for inspection robots, enabling autonomous localization, decision-making, motion planning and safe navigation in complex, dynamic real-world environments.

The Research Associate will support research on robot navigation, focusing on the integration of visual perception, localization, planning and navigation. The role will also investigate learning-based approaches, including diffusion models and reinforcement learning, for navigation decision-making, trajectory generation and adaptive robot behavior.

Key Responsibilities:

• Design and develop navigation algorithms for inspection robots in complex and dynamic environments.

• Work on global and local motion planning, obstacle avoidance, trajectory generation and trajectory tracking for humanoid robots.

• Investigate diffusion models and diffusion-based policies for navigation planning, trajectory generation and action prediction.

• Apply reinforcement learning and/or imitation learning methods to improve navigation performance and adaptive robot behavior.

• Integrate visual navigation and planning modules with humanoid locomotion and whole-body control systems.

• Build and evaluate algorithms in simulation environments and on real-world humanoid robotic platforms.

• Contribute to publications and technical reports

• Assist in mentoring students and supporting research activities

Job Requirements:

• Master’s degree in Robotics, Mechanical Engineering, Electrical Engineering, Computer Science, or related fields

• Strong background in at least one of the following:

  • robot motion planning and control;

  • autonomous decision-making;

  • robot localization and navigation.

• Experience in one or more of the following:

  • path planning, motion planning, trajectory optimization or model predictive control;

  • reinforcement learning, imitation learning or learning-based control;

  • diffusion policies or generative decision-making;

  • robotics physics simulators (e.g., Isaac Gym, MuJoCo, Gazebo)

• Proficiency in Python and/or C++

• Experience with PyTorch or similar deep learning frameworks

• Strong problem-solving ability and hands-on implementation skills

We regret to inform you that only shortlisted candidates will be notified.