We are seeking a Robotics Software Engineer specializing in motion planning to develop advanced navigation and trajectory-generation capabilities for robots operating in dynamic environments. You will design, refine, and deploy planning algorithms that ensure safe, precise, and efficient robotic motion. Experience bridging motion planning with computer vision-based perception is highly valued.
Responsibilities
- Build cutting-edge motion planning solutions, such as sampling-based, optimization-driven, and AI-enabled planners, for complex, high-DOF robotic platforms.
- Develop and maintain the software backbone for robotic motion control using C++ and Python within environments like ROS/ROS2.
- Model and simulate robotic behavior to validate planning logic before deploying on hardware.
- Implement real-time execution modules that interface with robot controllers, ensuring smooth and safe motion execution.
- Incorporate perception inputs from vision algorithms (e.g., detection, pose estimation, segmentation) into the planning pipeline for improved situational awareness.
- Create robust approaches for collision avoidance, obstacle representation, and navigation in changing or uncertain surroundings.
- Participate in the full software lifecycle, including requirement analysis, design reviews, testing, and system rollout.
- Collaborate closely with hardware, controls, and perception teams to achieve seamless system-level integration.
Requirements
- Master's Degree in Robotics, Computer Science, Electrical Engineering, or a related field.
- At least 2 years of professional experience building robotics software, with a strong concentration in motion planning.
- Experience developing for industrial robotic manipulators, including kinematics, dynamics, and motion execution workflows.
- In-depth understanding and real-world implementation experience with planning algorithms such as RRT/RRT., PRM, A., and trajectory optimization methods.
- Experience with machine learning tools (TensorFlow, PyTorch, scikit-learn) for perception or learning-based planning.
- Proficiency working with robotic simulators like Gazebo, ROS, or CoppeliaSim.
- Strong C++ skills suited for real-time systems, along with solid experience in Python.
- Strong grounding in robot kinematics, dynamics, control theory, and estimation techniques.
- Prior work with computer vision libraries (OpenCV, Open3D) and applying visual perception for robot motion or feedback control.
- Innovative mindset and strong problem-solving abilities in the fields of robotics and intelligent perception.
