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Generating Pointing Motions for a Humanoid Robot by Combining Motor Primitives.

J Camilo Vasquez Tieck1, Tristan Schnell1, Jacques Kaiser1

  • 1FZI Research Center for Information Technology, Karlsruhe, Germany.

Frontiers in Neurorobotics
|October 18, 2019
PubMed
Summary
This summary is machine-generated.

This study introduces a novel bio-inspired method for robot motion control using spiking neural networks. The approach enables robots to generate and control pointing motions by combining learned motor primitives, mimicking the human motor cortex.

Keywords:
closed-loophumanoid robot (HR)motion generationmotor primitivesneuroroboticspointing a targetspiking neural networks (SNN)

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Area of Science:

  • Robotics
  • Neuroscience
  • Artificial Intelligence

Background:

  • Human motor control is adaptable and flexible, offering inspiration for robotic systems.
  • Traditional robot motion generation requires explicit validation, unlike the human brain's adaptive approach.

Purpose of the Study:

  • To develop a biologically inspired method for generating and controlling robot pointing motions.
  • To implement a simplified model of the human motor cortex using spiking neural networks.

Main Methods:

  • A spiking neural network architecture was designed to model the human motor cortex.
  • The network learned a base motor primitive and four corrective primitives for pointing.
  • Motor primitives were combined in real-time to control a humanoid robot's pointing actions.

Main Results:

  • The proposed method successfully generated and controlled pointing motions for a humanoid robot.
  • The network effectively combined one, two, or three motor primitives to reach various targets.
  • Real-time robot control was achieved using the bio-inspired architecture.

Conclusions:

  • The bio-inspired spiking neural network approach offers an effective method for robot motion generation.
  • Combining motor primitives allows for flexible and adaptive robot pointing capabilities.
  • Future work aims to extend this method to grasping and tool manipulation tasks for industrial applications.