Job Summary
This role focuses on developing and implementing algorithms that empower autonomous robots to navigate complex environments. Key areas of responsibility include path planning, obstacle avoidance, and designing efficient docking strategies. You will work closely with cross-functional teams to ensure the robots operate safely and reliably in dynamic environments where humans and robots collaborate.

Key Responsibilities

• Design and implement advanced algorithms for robot navigation, ensuring path planning aligns with operational goals such as energy efficiency, speed, and safety.
• Develop and optimize docking strategies to achieve fast and accurate docking performance.
• Create real-time software solutions for autonomous navigation, leveraging sensor data from LiDAR, cameras, and other perception systems.
• Design and implement lightweight, real-time algorithms for obstacle detection and avoidance.
• Fine-tune navigation and docking algorithms to align with hardware capabilities and performance requirements.
• Build software bridges to enable seamless communication between different software components.

Required Qualifications

• Bachelor's or Master's degree in Robotics, Computer Science, Electrical Engineering, or a related discipline, with over three years of industry experience.
• Proficiency in programming languages such as C++ and Python, along with hands-on experience using ROS (Robot Operating System).
• Proven expertise in autonomous robot navigation, covering path planning, obstacle avoidance, and docking strategies.
• Solid understanding of motion planning algorithms and techniques, such as A*, D*, RRT, and SLAM.
• Familiarity with real-time systems, control theory, and optimization techniques.
• Strong grasp of robot kinematics and dynamics, and their impact on navigation and control systems.
• Experience with Test-Driven Development (TDD) practices.

Interested candidates, who wish to apply for the advertised position, please email us an updated copy of your resume.

We regret that only shortlisted candidates will be notified.

EA License No.: 01C4394

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