Robot Learning from Demonstration: Kinesthetic Teaching vs. Teleoperation

نویسندگان

  • Baris Akgun
  • Kaushik Subramanian
چکیده

We are interested in developing learning from demonstration systems that are suitable to be used by everyday people. We compare two interaction methods, kinesthetic teaching and teleoperation, for the users to show successful demonstrations of a skill. In the former, the user physically guides the robot and in the latter the user controls the robot with a haptic device. We evaluate our results using skill dependent quantitative measures, timing information and survey questions. We find that kinesthetic teaching is faster in terms of giving a single demonstration and the demonstrations are more successful. However, the learned skill does not perform better as expected. The survey results show that users think kinesthetic teaching is easier and more accurate and an open-ended question suggests that people would prefer kinesthetic teaching over teleoperation for everyday skills.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Novel Interaction Strategies for Learning from Teleoperation

The field of robot Learning from Demonstration (LfD) makes use of several input modalities for demonstrations (teleoperation, kinesthetic teaching, markerand vision-based motion tracking). In this paper we present two experiments aimed at identifying and overcoming challenges associated with using teleoperation as an input modality for LfD. Our first experiment compares kinesthetic teaching and...

متن کامل

Imitation Learning of Positional and Force Skills Demonstrated via Kinesthetic Teaching and Haptic Input

A method to learn and reproduce robot force interactions in a Human-Robot Interaction setting is proposed. The method allows a robotic manipulator to learn to perform tasks which require exerting forces on external objects by interacting with a human operator in an unstructured environment. This is achieved by learning two aspects of a task: positional and force profiles. The positional profile...

متن کامل

Learning the end-effector pose from demonstration for Bionic Handling Assistant robot

For most of the rigid manipulators, it is possible to apply a gravity compensation mode, by which the user is able to easily reconfigure the arm and record the necessary data. However, due to the specific characteristics of soft robots such as elastic properties and complex dynamics, it is usually very difficult to implement kinesthetic teaching for Learning from Demonstration (LfD) scenarios. ...

متن کامل

Is Kinesthetic Teaching what Smart Factories Really Need?

Programming by demonstration techniques have been investigated to facilitate and speed up the setup of new robot tasks. Kinesthetic teaching (KT), i.e., teaching by physically guiding a robot in the execution of a motion, has been adopted in industrial scenarios for its ease of use. In the work described here, we analyse and discuss limits and drawbacks of KT and suggest the adoption of a set o...

متن کامل

Imitation learning for a continuum trunk robot

The paper applies learning from demonstration (LfD) for high-level trajectory planning and movement control of the Bionic Handling Assistant (BHA) robot. For such soft continuum robot with mechanical elasticity and complex dynamics it is difficult to use kinesthetic teaching to collect demonstration data. We propose to use an active compliant controller to this aim and record both position and ...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2011