Autonomy Engineer, Motion Control
Posted on Tuesday, September 26, 2023
Who we are:At Glydways, we believe that mobility is a basic human right. Low-cost and ubiquitous access to affordable housing, employment, education, commerce and care lead to economic and social prosperity. As such our goal is to provide:Public transit with the highest capacity, the best user experience, the lowest cost, and the lowest carbon footprint.Our solution is a system of interconnected, profitable, and carbon footprint neutral transportation networks that uses standardized autonomous vehicles and a closed roadway. Together, they provide a 24/7 on-demand private mobility service without burdening the public with heavy upfront costs or annual system subsidies. Meet the team:You'll join a team that is responsible for developing software for resource scheduling, planning, controls, and modeling of systems. The team is composed of team members with strong backgrounds in various algorithm development fields and C++ programming. Members contribute to various projects within the team in a cross discipline fashion. Roles & Responsibilities:
- Work closely with teammates to design dynamics modeling and control methods.
- Develop system modeling algorithms and parameter estimation methods.
- Contribute to implementations of control systems.
- Being rigorous with implementation of unit tests and integration tests based on functional requirements and implementation detail.
- Contribute to code review, design review, planning, and general collaboration efforts.
- Working with other teams to understand and satisfy architectural, hardware, and platform requirements.
- PhD and 2 years of professional experience or BSc/MSc and 5 years of professional experience.
- C++ programming skills: experience with C++20 standard libraries, experience with a C++ unit testing framework such as gtest, experience working with CMake or Bazel build systems.
- Control system implementation skills: previously implemented optimal control algorithms (such as MPC or variations of LQR) with constraints for nonlinear, parameter-varying dynamical systems on hardware systems, have designed tests and metrics for evaluation of control system performance.
- Dynamic modeling background: experience modeling dynamic responses of MIMO systems in state-space representation, previously performed system identification and parameter estimation, experience modeling 6DOF kinematics using quaternions or rotation matrices, bonus: familiarity with vehicle dynamics such as suspension, power steering, tire models, and propulsion models.