Quantifying Teaching Behavior in Robot Learning from Demonstration

TY - JOUR

T1 - Quantifying Teaching Behavior in Robot Learning from Demonstration

AU - Sena, Aran

AU - Howard, Matthew

PY - 2020/1

Y1 - 2020/1

N2 - Learning from demonstration allows for rapid deployment of robot manipulators to a great many tasks, by relying on a person showing the robot what to do rather than programming it. While this approach provides many opportunities, measuring, evaluating, and improving the person’s teaching ability has remained largely unexplored in robot manipulation research. To this end, a model for learning from demonstration is presented here that incorporates the teacher’s understanding of, and influence on, the learner. The proposed model is used to clarify the teacher’s objectives during learning from demonstration, providing new views on how teaching failures and efficiency can be defined. The benefit of this approach is shown in two experiments (n=30 and n=36, respectively), which highlight the difficulty teachers have in providing effective demonstrations, and show how ̴169-180% –180% improvement in teaching efficiency can be achieved through evaluation and feedback shaped by the proposed framework, relative to unguided teaching.

AB - Learning from demonstration allows for rapid deployment of robot manipulators to a great many tasks, by relying on a person showing the robot what to do rather than programming it. While this approach provides many opportunities, measuring, evaluating, and improving the person’s teaching ability has remained largely unexplored in robot manipulation research. To this end, a model for learning from demonstration is presented here that incorporates the teacher’s understanding of, and influence on, the learner. The proposed model is used to clarify the teacher’s objectives during learning from demonstration, providing new views on how teaching failures and efficiency can be defined. The benefit of this approach is shown in two experiments (n=30 and n=36, respectively), which highlight the difficulty teachers have in providing effective demonstrations, and show how ̴169-180% –180% improvement in teaching efficiency can be achieved through evaluation and feedback shaped by the proposed framework, relative to unguided teaching.

KW - learning from demonstration

KW - robotics

KW - machine learning

KW - machine teaching

KW - human robot interaction

KW - manipulation

KW - Trajectory planning

KW - human computer interaction

KW - framework

KW - imitation learning

KW - learning from examples

UR - http://www.scopus.com/inward/record.url?scp=85076561224&partnerID=8YFLogxK

U2 - 10.1177/0278364919884623

DO - 10.1177/0278364919884623

M3 - Article

AN - SCOPUS:85076561224

SN - 0278-3649

VL - 39

SP - 54

EP - 72

JO - INTERNATIONAL JOURNAL OF ROBOTICS RESEARCH

JF - INTERNATIONAL JOURNAL OF ROBOTICS RESEARCH

IS - 1

ER -