Abstractions and security concepts for a robot operating system

As general purpose robots begin to find their way into the household and workplace, there will be a demand for software to run on these robots. My research group forsees the proliferation of robot apps that use a common set of abstractions to allow them to function on a variety of hardware platforms. In this thesis, I introduce a robot operating system to support these apps and detail the abstractions that it provides. I present many lessons learned from developing and debugging a number of such apps, and discuss a novel concept wherein apps and libraries are allowed to seek help from outside sources when they are unable to accomplish their goals. I show that our framework allows a robot to effectivly deal with challenges, such as user authentication. I demonstrate a simple bartender app to fetch drink orders for students, and it is succesfully able to deliver them in 10/10 trials in real- world conditions. I also present CLASS, a new system capable of identifying users robustly. I propose a framework for integrating a wide range of sensor values into an algorithm for identifying users, even if an attacker actively tries to impersonate a user. Our system is evaluated by using our reference robot and this platform to build a robot application that buys coffee at our local coffee shop for a user, without requiring explicit authentication. I evaluate CLASS under an adversarial model experimentally and find it to be robust and resilient to attack