Learning a pick-and-place robot task from human demonstration

Programming by human demonstration is an intuitive methodology to program robots. Since pick-and-place tasks are common, this paper proposes a framework to learn robot pick-and-place tasks by human demonstration. To recognize human motion, we adopt Gilbreth's therbligs to represent it. For each therblig, this work uses a corresponding robot motion primitive to implement it. Additionally, this work uses XABSL to describe the motion primitives and the sequence of them. The experiment showed that the human stacked three blocks in an order and the robot learned to stack the blocks in the same order by human demonstration.

[1]  Stefan Schaal,et al.  Incremental Online Learning in High Dimensions , 2005, Neural Computation.

[2]  Ales Ude,et al.  Trajectory generation from noisy positions of object features for teaching robot paths , 1993, Robotics Auton. Syst..

[3]  Stefan Schaal,et al.  Locally Weighted Projection Regression : An O(n) Algorithm for Incremental Real Time Learning in High Dimensional Space , 2000 .

[4]  Minoru Asada,et al.  Periodic nonlinear principal component neural networks for humanoid motion segmentation, generalization, and generation , 2004, ICPR 2004.

[5]  Danica Kragic,et al.  Task Learning Using Graphical Programming and Human Demonstrations , 2006, ROMAN 2006 - The 15th IEEE International Symposium on Robot and Human Interactive Communication.

[6]  Matthias Jüngel,et al.  XABSL - A Pragmatic Approach to Behavior Engineering , 2006, 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[7]  Stefan Schaal,et al.  http://www.jstor.org/about/terms.html. JSTOR's Terms and Conditions of Use provides, in part, that unless you have obtained , 2007 .

[8]  Hsien-I Lin,et al.  Semantic recognition of human gestures based on spatial and temporal reasoning , 2013, 2013 13th International Conference on Control, Automation and Systems (ICCAS 2013).

[9]  Rainer Palm,et al.  Programming by Demonstration of Pick-and-Place Tasks for Industrial Manipulators using Task Primitives , 2007, 2007 International Symposium on Computational Intelligence in Robotics and Automation.

[10]  Stefan Schaal,et al.  Robot Programming by Demonstration , 2009, Springer Handbook of Robotics.

[11]  M. Arbib,et al.  Grasping objects: the cortical mechanisms of visuomotor transformation , 1995, Trends in Neurosciences.

[12]  Aude Billard,et al.  On Learning, Representing, and Generalizing a Task in a Humanoid Robot , 2007, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[13]  Alexander Fabisch,et al.  Robot Recognition and Modeling in the RoboCup Standard Platform League , 2010 .

[14]  Katsu Yamane,et al.  Dynamics Filter - concept and implementation of online motion Generator for human figures , 2000, IEEE Trans. Robotics Autom..

[15]  Rüdiger Dillmann,et al.  Towards Cognitive Robots: Building Hierarchical Task Representations of Manipulations from Human Demonstration , 2005, Proceedings of the 2005 IEEE International Conference on Robotics and Automation.

[16]  Michael A. Arbib,et al.  Schema theory , 1998 .

[17]  Brett Browning,et al.  A survey of robot learning from demonstration , 2009, Robotics Auton. Syst..

[18]  Jun Tani,et al.  Dynamic and interactive generation of object handling behaviors by a small humanoid robot using a dynamic neural network model , 2006, Neural Networks.

[19]  Rajesh P. N. Rao,et al.  Robotic imitation from human motion capture using Gaussian processes , 2005, 5th IEEE-RAS International Conference on Humanoid Robots, 2005..