Localization Intern

Meet the team:

You will join a team that is responsible for developing software for localization, calibration, and mapping of robotic ground vehicles, which we lovingly refer to as Glydcars. The team is composed of team members with strong backgrounds in sensor fusion (LIDAR, RADAR, vision processing, UWB radios, inertial sensors, etc), SLAM (Simultaneous Localization and Mapping), optimization, filtering (Kalman filters, factor graphs, etc) and tracking. Members support development and maintenance of core components of a sophisticated autonomy stack for Glydcars, which operate in a variety of environments including GPS-denied areas. Team members contribute by writing C++ onboard software, peer-reviewing each other’s contributions, developing unit, subsystem, and end-to-end tests, and conducting data analysis (often using Python) in a common software repository. 

 

Roles & Responsibilities:

• Develop and enhance state-of-the-art algorithms for localization and mapping from LIDAR/RADAR/UWB Range Sensors/IMU/Encoders, etc.
• Improve upon existing integrity monitoring capabilities to provide a robust, safe localization system for passenger rides
• Work closely with teammates by conducting and receiving code reviews and demonstrating attention to detail.
• Conduct simulation (including developing and passing unit tests, subsystem tests, and end-to-end scenarios) and live testing of the autonomy stack.
• Perform detailed analysis of algorithm and system performance by replaying logs of simulated and live testing and augmenting analysis capabilities.
• Participate in the design of safety-critical software components of the Glydcar and wayside systems.
• Deliver answers and results to tough problems including providing cm-level accurate localization and mapping in GPS-denied environments.

 

Knowledge, Skills and Abilities:

• Masters / PhD graduating within 12 months of internship completion, in Robotics, Computer Science, Electrical Engineering, Aerospace, or a related field. Strong undergraduate seniors with relevant research experience will also be considered.
• C++ Programming Skills: experience with modern variants of C++ (e.g., C++17 or later), familiarity with a C++ unit testing framework such as gtest, and exposure to build systems such as CMake and/or Bazel.
• Coursework or hands-on experience in one or more of the following:
  • State estimation, Kalman filtering, or factor graph optimization
  • SLAM (Simultaneous Localization and Mapping)
  • Point cloud processing or LiDAR data analysis
  • Sensor fusion or multi-sensor calibration
  • Rigid body transforms, probability theory, and linear algebra
• Comfort working in a Linux environment with version control (git) and collaborative development workflows.
• Strong problem-solving skills and ability to work independently while communicating progress clearly.
• Ability to communicate technical ideas effectively, both in writing and in discussions.

Bonus Qualifications

• Experience with robotics middleware (ROS, ROS2, LCM, or similar).
• Familiarity with build systems such as Bazel or CMake.
• Experience with simulation frameworks for autonomous vehicles or robotics.
• Prior hands-on experience with LiDAR, RADAR, IMU, or GPS sensors.

Meet the team:

You will join a team that is responsible for developing software for localization, calibration, and mapping of robotic ground vehicles, which we lovingly refer to as Glydcars. The team is composed of team members with strong backgrounds in sensor fusion (LIDAR, RADAR, vision processing, UWB radios, inertial sensors, etc), SLAM (Simultaneous Localization and Mapping), optimization, filtering (Kalman filters, factor graphs, etc) and tracking. Members support development and maintenance of core components of a sophisticated autonomy stack for Glydcars, which operate in a variety of environments including GPS-denied areas. Team members contribute by writing C++ onboard software, peer-reviewing each other’s contributions, developing unit, subsystem, and end-to-end tests, and conducting data analysis (often using Python) in a common software repository. 

 

Roles & Responsibilities:

• Develop and enhance state-of-the-art algorithms for localization and mapping from LIDAR/RADAR/UWB Range Sensors/IMU/Encoders, etc.
• Improve upon existing integrity monitoring capabilities to provide a robust, safe localization system for passenger rides
• Work closely with teammates by conducting and receiving code reviews and demonstrating attention to detail.
• Conduct simulation (including developing and passing unit tests, subsystem tests, and end-to-end scenarios) and live testing of the autonomy stack.
• Perform detailed analysis of algorithm and system performance by replaying logs of simulated and live testing and augmenting analysis capabilities.
• Participate in the design of safety-critical software components of the Glydcar and wayside systems.
• Deliver answers and results to tough problems including providing cm-level accurate localization and mapping in GPS-denied environments.

 

Knowledge, Skills and Abilities:

• Masters / PhD graduating within 12 months of internship completion, in Robotics, Computer Science, Electrical Engineering, Aerospace, or a related field. Strong undergraduate seniors with relevant research experience will also be considered.
• C++ Programming Skills: experience with modern variants of C++ (e.g., C++17 or later), familiarity with a C++ unit testing framework such as gtest, and exposure to build systems such as CMake and/or Bazel.
• Coursework or hands-on experience in one or more of the following:
  • State estimation, Kalman filtering, or factor graph optimization
  • SLAM (Simultaneous Localization and Mapping)
  • Point cloud processing or LiDAR data analysis
  • Sensor fusion or multi-sensor calibration
  • Rigid body transforms, probability theory, and linear algebra
• Comfort working in a Linux environment with version control (git) and collaborative development workflows.
• Strong problem-solving skills and ability to work independently while communicating progress clearly.
• Ability to communicate technical ideas effectively, both in writing and in discussions.

Bonus Qualifications

• Experience with robotics middleware (ROS, ROS2, LCM, or similar).
• Familiarity with build systems such as Bazel or CMake.
• Experience with simulation frameworks for autonomous vehicles or robotics.
• Prior hands-on experience with LiDAR, RADAR, IMU, or GPS sensors.