S1E8 – Çetin Meriçli

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Did you know trucks transport over 70% of the nation’s freight? Then, layer on the demands e-commerce puts on the transportation industry, plus the persistent driver shortages, and you have the perfect storm for creating capacity constraints. Are driverless trucks a reality?

Self driving trucks will be a reality but this day is not close. There is still a lot of work to be done with the technology to deal with the inconsistencies of the real world. For decades, people have been working on self-driving applications and they have made many improvements and breakthroughs proving this is a difficult problem to solve.

Founded in 2018, Locomation in Pittsburgh, Pennsylvania is on the path to full autonomy by taking a bite-sized approach to tackling self-driving trucks.

In this episode of Crazy Hard Robots, Tom chats with Cetin Mericli, co-founder and CEO of Locomation to learn more about how they are making a positive impact on the transportation industry.

Tune in as Cetin talks to Tom about:
  • What is off nominal and what is an edge case and how do these impact self driving applications.
  • How self driving applications help truck drivers spend less time on the road and more time with their families.
  • How self-driving trucks can help the last-mile in the supply chain.
  • How Locomation will reduce greenhouse gas by 22% in comparison to traditional freight transportation.
About Çetin Meriçli, Ph.D

Çetin Meriçli, Ph.D. is a co-founder and the CEO of Locomation. Formerly a Special Faculty – Commercialization Specialist at the National Robotics Engineering Center (NREC) of Carnegie Mellon’s Robotics Institute, Dr. Meriçli has over 15 years of experience in developing and deploying complex robotic systems for real-world applications – and he has played key roles in over a dozen high profile applied robotics projects.

His expertise can be read in over 40 publications on subjects covering his accomplishments including safe and efficient machine learning for robust robot autonomy and perception, robot learning from human demonstration and feedback, interactive learning, sliding autonomy through learning, long-term autonomy and lifelong learning, data-driven high-fidelity robot simulation, human-robot interaction, probabilistic robotics, multi-robot coordination and planning, and software engineering practices for robot software development.

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