Research Engineer (Learning-based Motion Planning)

Job Description

The research project focuses on developing safe interactive navigation and manipulation capabilities for mobile robots operating in complex, dynamic environments.

The research engineer is expected to contribute to the following key aspects:

a) Design robust obstacle avoidance algorithms for mobile robots in dynamically changing environments, focusing on formal safety constraints and real-time performance in unpredictable conditions.

b) Develop specialized differentiable numerical solvers for trajectory optimization that generate informed motion trajectories for contact-rich manipulation tasks, handling complex dynamics and physical constraints efficiently.

c) Integrate planning and control algorithms with differentiable simulation technologies to build a trajectory data collection system that generates high-quality, diverse task data for vision-language-action learning, enabling seamless integration from human instructions to robotic actions in complex mobile manipulation scenarios.

Qualifications

Master or Bachelor Degree in a relevant discipline, e.g. robotics, computer science, electrical/electronic engineering, etc.

Extensive experience in robotic motion planning and control, especially in obstacle avoidance and contact-aware task execution with demonstrated expertise in real-world robotic applications.

Substantial practical experience in real robot development and deployment, including humanoid robot systems.

Strong mathematical background with solid knowledge in numerical optimization theory. Familiarity with semidefinite programming and its convex relaxation techniques is highly preferred.

Proficient experience with various robotics simulators (e.g., MuJoCo, ISSAC) and excellent programming skills in C++ and Python with the ability to develop efficient, production-quality code.

Open to Fixed Term Contract.

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