Spring Intern/Co-Op: 2023 Motion Control, Trajectory Optimization Formulation Intern

The Motional global headquarters are located at 100 Northern Avenue in Boston, MA. Nestled in the busting Seaport district with sweeping views of Boston Harbor and downtown Boston, the offices are located close to major transit lines and a quick walk to various restaurants and popular attractions.

Motion Control, Trajectory Optimization Formulation Intern

Mission Summary:
Motional is seeking a trajectory formulation intern to join the controls group at Motional. As an intern, you will directly contribute to Motional’s driverless future by helping to formulate trajectory optimization problems that explicitly consider uncertainty. You will engage with the controls team on solving challenging motion planning, trajectory optimization, and controls problems. This intern will have the ability to experiment with optimal control approaches that consider uncertainty and work with self-driving vehicles in real-life uncertain environments

What You'll Be Doing

• You will be working day to day with the Controls team to design, test, and implement new motion planning approaches for uncertainty
• You will gain the experience of working in a modern development environment with real motion planning algorithms
• You will directly be able to analyze and test the vehicle’s performance as the results of new algorithmic changes
• You will directly contribute to making the vehicle’s planning algorithms more robust to real world uncertainties

What We're Looking For

• Candidates enrolled in a Masters or PhD program in Computer Science, Robotics or similar technical field of study
• Candidates with prior experience in controls, motion planning, optimization, model predictive control
• Candidates capable of working in a fast-paced development environment, and willing to quickly try out and prove ideas
• Candidates with experience working with Python and C++ for developing motion control algorithms
• Candidates passionate about motion planning and controls problems in the automated vehicle space

Bonus Points (not required)

• Experience with Forces and Casadi
• Experience with dynamical system modeling
• If you don’t meet 100% of the qualifications outlined above - that’s okay! We encourage you to apply if you think this is a role that would make you excited to come into work every day and that you can deliver the results we need.

Why you should join us:

• Be part of the heart of a core team tackling the trajectory optimization problem
• Grow your knowledge by working with and developing real-time motion planning approaches under uncertainty
• Gain the skills of working on state-of-the-art trajectory optimization methods in industry