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Learning tasks from a single demonstration
Learning a complex dynamic robot manoeuvre from a single human demonstration is difficult. This paper explores an approach to learning from demonstration based on learning an optimization criterion from the demonstration and a task model from repeated attempts to perform the task, and using the learned criterion and model to compute an appropriate robot movement. A preliminary version of the approach has been implemented on an anthropomorphic robot arm using a pendulum swing up task as an example
@inproceedings{Atkeson_IICRA_1997, title = {Learning tasks from a single demonstration}, booktitle = {IEEE International Conference on Robotics and Automation (ICRA97)}, abstract = {Learning a complex dynamic robot manoeuvre from a single human demonstration is difficult. This paper explores an approach to learning from demonstration based on learning an optimization criterion from the demonstration and a task model from repeated attempts to perform the task, and using the learned criterion and model to compute an appropriate robot movement. A preliminary version of the approach has been implemented on an anthropomorphic robot arm using a pendulum swing up task as an example}, volume = {2}, pages = {1706-1712}, publisher = {Piscataway, NJ: IEEE}, address = {Albuquerque, NM, 20-25 April}, year = {1997}, note = {clmc}, slug = {atkeson_iicra_1997}, author = {Atkeson, C. G. and Schaal, S.}, crossref = {p44}, url = {http://www-clmc.usc.edu/publications/A/atkeson-ICRA1997.pdf} }