Senior Software Engineer - Path Planning

About the Role

LionsBot International is looking for a skilled Software Engineer to craft sophisticated navigation and path planning algorithms that empower our autonomous cleaning robot fleet to navigate safely and smartly within complex environments worldwide. This position is perfect for someone passionate about robotics, algorithm design, and integrating systems. You will oversee the entire planning software stack, from high-level route strategizing to detailed path generation, collaborating closely with teams handling SLAM, Perception, and Control to provide navigation solutions that reliably perform in real-world scenarios.

Key Responsibilities

• Create and implement global path planning solutions suitable for expansive and dynamic settings, ensuring efficient and obstacle-free routing across multi-level indoor spaces.
• Develop and fine-tune coverage path planning algorithms specifically designed for cleaning robots.
• Manage and update costmaps and environmental models, combining data from perception and SLAM systems for precise navigation planning.
• Apply and innovate learning-based planning techniques such as reinforcement and imitation learning to bolster navigation flexibility and robustness in changing environments.
• Design and execute thorough test cases to validate algorithms and software in both simulated settings and real robotic deployments, ensuring dependable performance.
• Document all implemented code and testing procedures comprehensively for ongoing reference and development.

Qualifications & Experience

• A Bachelor’s, Master’s, or PhD degree in Computer Science, Robotics, or a closely related discipline.
• Over 3 years of professional experience in navigation, motion planning, or coverage planning in an industrial context.
• Advanced skills in C++ and Python programming under Linux environments.
• Practical experience using ROS1 and ROS2 along with adherence to modern software engineering standards.
• Strong knowledge of robot kinematics, dynamics, and map formats including occupancy grids, costmaps, and graph structures.
• In-depth understanding of graph-based and sampling-based global planning algorithms such as A*, D*, RRT*, and PRM.
• Proven track record in crafting comprehensive coverage path planning methods.
• Familiarity with trajectory optimization and local planner architectures such as TEB and Model Predictive Control.
• Experience with simulation platforms like Gazebo, Isaac Sim, or RViz for development and testing purposes.
• Excellent analytical, problem-solving, and debugging skills.
• Knowledge of learning-based or hybrid planning algorithms (reinforcement and imitation learning) is advantageous.
• Experience optimizing software for embedded systems such as Nvidia Jetson, ARM architectures, or GPU acceleration is a plus.

Additional Information

If you are driven to create impactful operational advancements, excel at complex problem analysis, and thrive in a rapidly growing startup environment, LionsBot welcomes your talent to innovate the future of robotics.