Makoto Kurihara is an autonomous driving software engineer with nine years of experience building vehicle control and transmission systems, currently advancing motion planning and control at Tier IV. He combines a strong academic foundation from the University of Tokyo with hands-on expertise in C++, ROS, Python, MATLAB, and machine learning to translate estimated vehicle state and environment perception into robust control behaviors. At Honda Research Institute he shipped transmission software that reduced fuel consumption and suppressed vibration, and at Tier IV he has contributed notable fixes and integrations to the widely used Autoware.Universe project, improving motion velocity smoothing and minimal risk maneuvers. Comfortable across embedded and back-end domains, he also explores Rust and planning algorithms, bringing a pragmatic blend of research-driven thinking and production-grade engineering.
Contributions:81 reviews, 13 commits, 34 PRs in 8 months
Contributions summary:Makoto contributed significantly to the Autoware.Universe project, primarily focusing on the motion planning and control aspects of autonomous driving. Their commits involved refactoring and initializing parameters within the motion velocity smoother, addressing velocity limits, and integrating the system with MRM (Minimal Risk Maneuver) behaviors. They also worked on spline interpolation and made adjustments to the pose initializer to improve API responses. The user's work encompassed a range of functionalities critical for the safe and reliable operation of autonomous vehicles.
Contributions:90 PRs, 80 pushes, 94 branches in 4 years
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