Generating Pointing Motions for a Humanoid Robot by Combining Motor Primitives
The human motor system is robust, adaptive and very flexible. The underlying principles of human motion provide inspiration for robotics. Pointing at different targets is a common robotics task, where insights about human motion can be applied. Traditionally in robotics, when a motion is generated i...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2019-09-01
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| Series: | Frontiers in Neurorobotics |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/article/10.3389/fnbot.2019.00077/full |
| _version_ | 1818959561110847488 |
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| author | J. Camilo Vasquez Tieck Tristan Schnell Jacques Kaiser Felix Mauch Arne Roennau Rüdiger Dillmann Rüdiger Dillmann |
| author_facet | J. Camilo Vasquez Tieck Tristan Schnell Jacques Kaiser Felix Mauch Arne Roennau Rüdiger Dillmann Rüdiger Dillmann |
| author_sort | J. Camilo Vasquez Tieck |
| collection | DOAJ |
| description | The human motor system is robust, adaptive and very flexible. The underlying principles of human motion provide inspiration for robotics. Pointing at different targets is a common robotics task, where insights about human motion can be applied. Traditionally in robotics, when a motion is generated it has to be validated so that the robot configurations involved are appropriate. The human brain, in contrast, uses the motor cortex to generate new motions reusing and combining existing knowledge before executing the motion. We propose a method to generate and control pointing motions for a robot using a biological inspired architecture implemented with spiking neural networks. We outline a simplified model of the human motor cortex that generates motions using motor primitives. The network learns a base motor primitive for pointing at a target in the center, and four correction primitives to point at targets up, down, left and right from the base primitive, respectively. The primitives are combined to reach different targets. We evaluate the performance of the network with a humanoid robot pointing at different targets marked on a plane. The network was able to combine one, two or three motor primitives at the same time to control the robot in real-time to reach a specific target. We work on extending this work from pointing to a given target to performing a grasping or tool manipulation task. This has many applications for engineering and industry involving real robots. |
| first_indexed | 2024-12-20T11:43:35Z |
| format | Article |
| id | doaj.art-6763f7462cee4a628c2aa838bad465a1 |
| institution | Directory Open Access Journal |
| issn | 1662-5218 |
| language | English |
| last_indexed | 2024-12-20T11:43:35Z |
| publishDate | 2019-09-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Neurorobotics |
| spelling | doaj.art-6763f7462cee4a628c2aa838bad465a12022-12-21T19:41:55ZengFrontiers Media S.A.Frontiers in Neurorobotics1662-52182019-09-011310.3389/fnbot.2019.00077466232Generating Pointing Motions for a Humanoid Robot by Combining Motor PrimitivesJ. Camilo Vasquez Tieck0Tristan Schnell1Jacques Kaiser2Felix Mauch3Arne Roennau4Rüdiger Dillmann5Rüdiger Dillmann6FZI Research Center for Information Technology, Karlsruhe, GermanyFZI Research Center for Information Technology, Karlsruhe, GermanyFZI Research Center for Information Technology, Karlsruhe, GermanyFZI Research Center for Information Technology, Karlsruhe, GermanyFZI Research Center for Information Technology, Karlsruhe, GermanyFZI Research Center for Information Technology, Karlsruhe, GermanyKarlsruhe Institute of Technology (KIT), Karlsruhe, GermanyThe human motor system is robust, adaptive and very flexible. The underlying principles of human motion provide inspiration for robotics. Pointing at different targets is a common robotics task, where insights about human motion can be applied. Traditionally in robotics, when a motion is generated it has to be validated so that the robot configurations involved are appropriate. The human brain, in contrast, uses the motor cortex to generate new motions reusing and combining existing knowledge before executing the motion. We propose a method to generate and control pointing motions for a robot using a biological inspired architecture implemented with spiking neural networks. We outline a simplified model of the human motor cortex that generates motions using motor primitives. The network learns a base motor primitive for pointing at a target in the center, and four correction primitives to point at targets up, down, left and right from the base primitive, respectively. The primitives are combined to reach different targets. We evaluate the performance of the network with a humanoid robot pointing at different targets marked on a plane. The network was able to combine one, two or three motor primitives at the same time to control the robot in real-time to reach a specific target. We work on extending this work from pointing to a given target to performing a grasping or tool manipulation task. This has many applications for engineering and industry involving real robots.https://www.frontiersin.org/article/10.3389/fnbot.2019.00077/fullneuroroboticsmotion generationspiking neural networks (SNN)pointing a targetmotor primitiveshumanoid robot (HR) |
| spellingShingle | J. Camilo Vasquez Tieck Tristan Schnell Jacques Kaiser Felix Mauch Arne Roennau Rüdiger Dillmann Rüdiger Dillmann Generating Pointing Motions for a Humanoid Robot by Combining Motor Primitives Frontiers in Neurorobotics neurorobotics motion generation spiking neural networks (SNN) pointing a target motor primitives humanoid robot (HR) |
| title | Generating Pointing Motions for a Humanoid Robot by Combining Motor Primitives |
| title_full | Generating Pointing Motions for a Humanoid Robot by Combining Motor Primitives |
| title_fullStr | Generating Pointing Motions for a Humanoid Robot by Combining Motor Primitives |
| title_full_unstemmed | Generating Pointing Motions for a Humanoid Robot by Combining Motor Primitives |
| title_short | Generating Pointing Motions for a Humanoid Robot by Combining Motor Primitives |
| title_sort | generating pointing motions for a humanoid robot by combining motor primitives |
| topic | neurorobotics motion generation spiking neural networks (SNN) pointing a target motor primitives humanoid robot (HR) |
| url | https://www.frontiersin.org/article/10.3389/fnbot.2019.00077/full |
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