x-bot.org

Neural Networks, Robotics, Evolutionary Algorithms, Neural Science, Cool Stuff

Personal Website of Christian Rempis

Neural Motion Capturing

Memorizing Motion Trajectories as Pattern Generators in the Activation Dynamics of Neural Ring Memory Modules

Overview

Neural Motion Capturing

The following videos demonstrate networks with the capability to capture a 'trained' motion and to recall that motion later. With such networks arbitrary gestures, motions and movements can be modelled when they are required e.g. in an ALEAR language game. This prevents time consuming programming of such motions. It is sufficient to show the robot the motion. Captured motions can also be transferred to fixed motion networks when such behaviors are needed later. The videos only show motion capturing with a single arm, but the network can be extended to all limbs of the robot. In principle, also a fusion of motion mimicry and reactice, sensor driven behavior (e.g. camera guided motions) is possible.

withPlotsNicer_withRawImages_short.avi

ArmMovement_MotionCapture1_Myon.avi ArmMovement_MotionCapture2_Myon.avi ArmMovement_MotionCapture3_Myon.avi
ArmMovement_MotionCapture4_Myon.avi ArmMovement_MotionCapture5_Myon.avi GraspingObject_MotionCapture1_Myon.avi
GraspingObject_MotionCapture2_Myon.avi GraspingObject_MotionCapture3_Myon.avi GraspingObject_MotionCapture4_Myon.avi

Important Note:

To view the networks you need either the Network Editor of the NERD Toolkit (NERD Format *.onn) or a vector graphics programm (SVG) such as InkScape. The scalable vector graphics images are comparably large and require a fast computer to be rendered in acceptable time!



Scalable Vector Graphics of full network
Full network in NERD Toolkit XML format

Related Publications:

  • C. W. Rempis, , “A Neural Network to Capture Demonstrated Motions on a Humanoid Robot to Rapidly Create Complex Central Pattern Generators as Reusable Neural Building Blocks”, in Proceedings of the International Conference on Robotics and Automation (ICRA 2013), 2013

Funding: