---
_id: '658'
abstract:
- lang: eng
  text: 'With the accelerated development of robot technologies, control becomes one
    of the central themes of research. In traditional approaches, the controller,
    by its internal functionality, finds appropriate actions on the basis of specific
    objectives for the task at hand. While very successful in many applications, self-organized
    control schemes seem to be favored in large complex systems with unknown dynamics
    or which are difficult to model. Reasons are the expected scalability, robustness,
    and resilience of self-organizing systems. The paper presents a self-learning
    neurocontroller based on extrinsic differential plasticity introduced recently,
    applying it to an anthropomorphic musculoskeletal robot arm with attached objects
    of unknown physical dynamics. The central finding of the paper is the following
    effect: by the mere feedback through the internal dynamics of the object, the
    robot is learning to relate each of the objects with a very specific sensorimotor
    pattern. Specifically, an attached pendulum pilots the arm into a circular motion,
    a half-filled bottle produces axis oriented shaking behavior, a wheel is getting
    rotated, and wiping patterns emerge automatically in a table-plus-brush setting.
    By these object-specific dynamical patterns, the robot may be said to recognize
    the object''s identity, or in other words, it discovers dynamical affordances
    of objects. Furthermore, when including hand coordinates obtained from a camera,
    a dedicated hand-eye coordination self-organizes spontaneously. These phenomena
    are discussed from a specific dynamical system perspective. Central is the dedicated
    working regime at the border to instability with its potentially infinite reservoir
    of (limit cycle) attractors "waiting" to be excited. Besides converging
    toward one of these attractors, variate behavior is also arising from a self-induced
    attractor morphing driven by the learning rule. We claim that experimental investigations
    with this anthropomorphic, self-learning robot not only generate interesting and
    potentially useful behaviors, but may also help to better understand what subjective
    human muscle feelings are, how they can be rooted in sensorimotor patterns, and
    how these concepts may feed back on robotics.'
article_number: '00008'
article_processing_charge: Yes
author:
- first_name: Ralf
  full_name: Der, Ralf
  last_name: Der
- first_name: Georg S
  full_name: Martius, Georg S
  id: 3A276B68-F248-11E8-B48F-1D18A9856A87
  last_name: Martius
citation:
  ama: Der R, Martius GS. Self organized behavior generation for musculoskeletal robots.
    <i>Frontiers in Neurorobotics</i>. 2017;11(MAR). doi:<a href="https://doi.org/10.3389/fnbot.2017.00008">10.3389/fnbot.2017.00008</a>
  apa: Der, R., &#38; Martius, G. S. (2017). Self organized behavior generation for
    musculoskeletal robots. <i>Frontiers in Neurorobotics</i>. Frontiers Research
    Foundation. <a href="https://doi.org/10.3389/fnbot.2017.00008">https://doi.org/10.3389/fnbot.2017.00008</a>
  chicago: Der, Ralf, and Georg S Martius. “Self Organized Behavior Generation for
    Musculoskeletal Robots.” <i>Frontiers in Neurorobotics</i>. Frontiers Research
    Foundation, 2017. <a href="https://doi.org/10.3389/fnbot.2017.00008">https://doi.org/10.3389/fnbot.2017.00008</a>.
  ieee: R. Der and G. S. Martius, “Self organized behavior generation for musculoskeletal
    robots,” <i>Frontiers in Neurorobotics</i>, vol. 11, no. MAR. Frontiers Research
    Foundation, 2017.
  ista: Der R, Martius GS. 2017. Self organized behavior generation for musculoskeletal
    robots. Frontiers in Neurorobotics. 11(MAR), 00008.
  mla: Der, Ralf, and Georg S. Martius. “Self Organized Behavior Generation for Musculoskeletal
    Robots.” <i>Frontiers in Neurorobotics</i>, vol. 11, no. MAR, 00008, Frontiers
    Research Foundation, 2017, doi:<a href="https://doi.org/10.3389/fnbot.2017.00008">10.3389/fnbot.2017.00008</a>.
  short: R. Der, G.S. Martius, Frontiers in Neurorobotics 11 (2017).
date_created: 2018-12-11T11:47:45Z
date_published: 2017-03-16T00:00:00Z
date_updated: 2021-01-12T08:08:04Z
day: '16'
ddc:
- '006'
department:
- _id: ChLa
- _id: GaTk
doi: 10.3389/fnbot.2017.00008
ec_funded: 1
file:
- access_level: open_access
  checksum: b1bc43f96d1df3313c03032c2a46388d
  content_type: application/pdf
  creator: system
  date_created: 2018-12-12T10:18:49Z
  date_updated: 2020-07-14T12:47:33Z
  file_id: '5371'
  file_name: IST-2017-903-v1+1_fnbot-11-00008.pdf
  file_size: 8439566
  relation: main_file
file_date_updated: 2020-07-14T12:47:33Z
has_accepted_license: '1'
intvolume: '        11'
issue: MAR
language:
- iso: eng
month: '03'
oa: 1
oa_version: Published Version
project:
- _id: 25681D80-B435-11E9-9278-68D0E5697425
  call_identifier: FP7
  grant_number: '291734'
  name: International IST Postdoc Fellowship Programme
publication: Frontiers in Neurorobotics
publication_identifier:
  issn:
  - '16625218'
publication_status: published
publisher: Frontiers Research Foundation
publist_id: '7078'
pubrep_id: '903'
quality_controlled: '1'
scopus_import: 1
status: public
title: Self organized behavior generation for musculoskeletal robots
tmp:
  image: /images/cc_by.png
  legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
  name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
  short: CC BY (4.0)
type: journal_article
user_id: 2EBD1598-F248-11E8-B48F-1D18A9856A87
volume: 11
year: '2017'
...