74. Learning from Humans

This chapter surveys the main approaches developed to date to endow robots with the ability to learn from human guidance. The field is best known as robot programming by demonstration, robot learning from/by demonstration, apprenticeship learning and imitation learning. We start with a brief historical overview of the field. We then summarize the various approaches taken to solve four main questions: when, what, who and when to imitate. We emphasize the importance of choosing well the interface and the channels used to convey the demonstrations, with an eye on interfaces providing force control and force feedback. We then review algorithmic approaches to model skills individually and as a compound and algorithms that combine learning from human guidance with reinforcement learning. We close with a look on the use of language to guide teaching and a list of open issues. 74.1 Learning of Robots .............................. 1995 74.1.1 Principle ................................... 1996 74.1.2 Brief History.............................. 1996 74.2 Key Issues When Learning from Human Demonstrations ............... 1998 74.2.1 When and Whom to Imitate . ...... 1998 74.2.2 How to Imitate and How to Solve the Correspondence Problem ...... 1999 74.3 Interfaces for Demonstration. ............... 2000 74.4 Algorithms to Learn from Humans ........ 2002 74.4.1 Learning Individual Motions ....... 2002 74.4.2 Learning Compound Actions ....... 2003 74.4.3 Incremental Teaching Methods ... 2004 74.4.4 Combining Learning from Humans with Other Learning Techniques .................. 2005 74.4.5 Learning from Humans, a Form of Human–Robot Interaction. ..... 2006 74.5 Conclusions and Open Issues in Robot LfD ........................................ 2008 Video-References . ........................................ 2009 References ................................................... 2009