AI for Robotics and Autonomy with Francis X. Govers III

In this episode of ODSC’s Ai X Podcast, we are joined by Francis Govers, a contributor to the design of over 30 manned and unmanned land, sea, air, and space vehicles, and an expert in robotics and autonomy. Francis is an Air Force veteran, spent 10 years at NASA, was a lead engineer for the International Space Station, was Deputy Chief Engineer for the US Army Future Combat Systems, participated in the DARPA Grand Challenge, and managed a Zeppelin airship. He worked on the "Yellow Line" for football and designed telemetry systems for NASCAR and IndyCar. He designed RAMSEE, the robot security guard, as CTO of Gamma 2 Robotics. As a commercial pilot, writer, artist, musician, engineer, race car nut, and designer, Francis has a serious addiction to building things that frequently get him into trouble. He has published 48 magazine articles and contributed to five books. He received five outstanding achievement awards from NASA, the Explorer Award by the National Space Society, recognition from Scientific American for “World Changing Ideas”, and was recognized by the Vertical Flight Society as a "Titan of Autonomy". SHOW TOPICS: - The second edition of “Artificial Intelligence for Robotics” which came out in February - Tell us about your background and key career moments - Tell us about your book - what’s the motivation and audience? - The growing industry of robotics startups and their appeal to investors - What is the fundamental difference between an AI-enabled robot and a traditional robot? - How does autonomy differ from pre-programmed robotic behaviors? - Why is supervised learning important in AI robotics, and how is it used in this book? - You show the reader how to build a robot in your book. What are the primary technical components (hardware and software) needed to build an AI robot? - Tell us about Robotic Operating Systems aka ROS - How can deep learning be used for robotics and is transfer learning applicable? - How can we teach a robot to listen and what are the main challenges in developing a robot capable of understanding human speech? - What is Spectral Analysis? - Beyond just listening, how do we give a robot a personality, known as artificial personality (AP)? - What is the purpose of Monte Carlo modeling in creating human-like interactions for the robot? - How does the robot’s personality system enable it to hold simple conversations with children? - Why is it important for the robot to understand the mood of its human user during interactions? - How do robots traditionally navigate unstructured envoirnments and what new methods does AI introduce? SHOW NOTES: Francis Govers: https://www.linkedin.com/in/francisxgoversiii/ Artificial Intelligence for Robotics: https://www.packtpub.com/en-us/product/artificial-intelligence-for-robotics-9781788835442 NASA Space Station: https://www.nasa.gov/international-space-station/ Q-Learning: https://en.wikipedia.org/wiki/Q-learning This episode was sponsored by:   Ai+ Training⁠ ⁠https://aiplus.training/⁠⁠  And created in partnership with ODSC⁠ ⁠https://odsc.com/⁠⁠  Join us at our upcoming and highly anticipated conference ODSC West in South San Francisco October 29-31.