Robotics Research Resident: Localization and Mapping

About the Role

The Robotics Research Resident: Localization and Mapping will focus on designing, implementing, and evaluating algorithms for robot localization, mapping, and navigation in real-world retail and distribution environments.

Day-to-day responsibilities include developing and testing SLAM and related perception pipelines, integrating sensor data from sources such as LiDAR, cameras, and IMUs, and optimizing algorithms for robustness and performance in complex, dynamic settings.

Key Responsibilities

• Develop and test SLAM and related perception pipelines for robot localization, mapping, and navigation.
• Integrate sensor data from sources such as LiDAR, cameras, and IMUs to enhance mapping and navigation performance.
• Optimize algorithms for robustness and performance in complex, dynamic settings.
• Work closely with cross-functional teams to build prototypes, run experiments, analyze results, and translate research outcomes into deployable components within the company's intelligent RTM ecosystem.
• Design and implement experiments to evaluate the performance of localization, mapping, and navigation algorithms.
• Collaborate with engineering, data science, and product teams to align research with practical business applications.
• Communicate research outcomes and results to both technical and non-technical stakeholders.

Skills & Qualifications

• Strong foundation in robotics, computer science, or a related field.
• Knowledge of localization, mapping, and motion planning concepts.
• Experience with algorithms for SLAM, state estimation, and sensor fusion (e.g., Kalman filters, particle filters, graph-based optimization).
• Skills in working with common robotics frameworks and tools, such as ROS/ROS2, Gazebo, or similar simulation and integration environments.
• Proficiency in programming languages commonly used in robotics research, such as C++, Python, and relevant libraries (e.g., Eigen, OpenCV, PCL).
• Ability to process and integrate data from perception sensors including cameras, LiDAR, depth sensors, and IMUs in real-world conditions.
• Familiarity with machine learning or computer vision techniques that enhance mapping, environment understanding, or navigation performance.
• Master's or PhD (or equivalent) degree in a relevant field.

What You'll Learn

This role offers the opportunity to gain hands-on experience in designing, implementing, and evaluating algorithms for robot localization, mapping, and navigation in real-world retail and distribution environments.

You will work closely with cross-functional teams to build prototypes, run experiments, analyze results, and translate research outcomes into deployable components within the company's intelligent RTM ecosystem.

This experience will help you develop strong analytical and problem-solving skills, as well as the ability to design experiments, interpret results, and iterate on research ideas.

Resume Tip

When applying for this role, be sure to highlight your experience with algorithms for SLAM, state estimation, and sensor fusion, as well as your skills in working with common robotics frameworks and tools.

Also, be prepared to provide specific examples of how you have applied machine learning or computer vision techniques to enhance mapping, environment understanding, or navigation performance in previous projects or research.