How to teach a new robot new tricks - an interactive learning framework applied to service robotics

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Remy, Sekou
Howard, Ayanna M.
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The applications of robotics are changing. Just as computers evolved from the realm of research and extreme novelty tools to now becoming essential components of modern life, robotics is also making a similar transition. With the changes in applications come changes in the user base of robotics. These users will span a broad range of society, but there are some key properties that can be used to characterize them. First they, more often than not, will not be the designers of the robots. Second, they will not have robot control as their primary task while operating the robot. Third, they will not have the resources or the desire to provide all the training that the robot will require, yet they will have the need to fine tune robot performance to their specific needs. Fourth, they will want to use multiple modes of interaction to make the robot accomplish the primary task. Fifth, they will expect and demand that the robot remain safe at all times (safe to humans, pets, or personal property) and expect the robot to be a readily replaceable appliance (cheap). Sixth, they will expect that the robot will be intelligent, at least in the confines of the task at hand. These are some of the key properties that will exist for the new user base. To address some of the needs that will arise because of these properties, we propose work that enables behavior transfer from teacher to robotic student that is facilitated through observation and interaction. Many users in the projected user base will not have exposure to the technologies that enable robotic operation. These users will however have some degree of understanding of how they would like the robot to provide assistance in accomplishing the task. The goal of this work is specifically to enable the user to transfer this understanding to the robot, and have the robot acquire this understanding via interactive learning. To make interactive learning possible via interaction we believe that the robot will have to be able to perform some degree of self regulation. Further, since it is assumed that the user will not have access to the robot's internal machinations, the robot will also have to be able to properly manage the knowledge it acquires over time and to verify and validate its understanding periodically. Scaffolding, a method in which teachers provide support while the student learns to master portions of a task, is likely to be the primary method to facilitate this process. This research will undertake study of coherence and its relevance to learning by observation. It will also implement the components that would enable a robot to learn to perform a small set of tasks and demonstrate them in various settings. For this work a robot will be defined as a hardware platform upon which a software agent operates. It is our desire that this software agent will be equipped to operate on any platform and learn any task that a human could perform with the same resources.
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