This paper summarizes observations and lessons learned by the WPI-CMU team and self-reports made by many of the DARPA Robotics Challenge teams on what happened at the DARPA Robotics Challenge Finals. Major conclusions are: (1) Reducing operator errors is the most cost effective way to improve robot performance. Methods include operator training and practice, and software safeguards to detect and prevent operator errors. (2) Super-human sensing is another way to greatly improve robot performance. To some extent this matches what happened in the DARPA autonomous driving challenges, in which improved sensing was the key to improved performance. (3) Paradigm shifts are needed in academic robotics, such as emphasizing designing robust behaviors, systems design including what seem like unimportant issues such as thermal management, and consistent real world results rather than videos of the rare successes.