Reachy, a 3D-Printed Human-Like Robotic Arm as a Testbed for Human-Robot Control Strategies.

3D printing humanoid robot open-source rehabilitation engineering research testbed robotic arm

Journal

Frontiers in neurorobotics
ISSN: 1662-5218
Titre abrégé: Front Neurorobot
Pays: Switzerland
ID NLM: 101477958

Informations de publication

Date de publication:
2019
Historique:
received: 03 04 2019
accepted: 29 07 2019
entrez: 3 9 2019
pubmed: 3 9 2019
medline: 3 9 2019
Statut: epublish

Résumé

To this day, despite the increasing motor capability of robotic devices, elaborating efficient control strategies is still a key challenge in the field of humanoid robotic arms. In particular, providing a human "pilot" with efficient ways to drive such a robotic arm requires thorough testing prior to integration into a finished system. Additionally, when it is needed to preserve anatomical consistency between pilot and robot, such testing requires to employ devices showing human-like features. To fulfill this need for a biomimetic test platform, we present Reachy, a human-like life-scale robotic arm with seven joints from shoulder to wrist. Although Reachy does not include a poly-articulated hand and is therefore more suitable for studying reaching than manipulation, a robotic hand prototype from available third-party projects could be integrated to it. Its 3D-printed structure and off-the-shelf actuators make it inexpensive relatively to the price of an industrial-grade robot. Using an open-source architecture, its design makes it broadly connectable and customizable, so it can be integrated into many applications. To illustrate how Reachy can connect to external devices, this paper presents several proofs of concept where it is operated with various control strategies, such as tele-operation or gaze-driven control. In this way, Reachy can help researchers to explore, develop and test innovative control strategies and interfaces on a human-like robot.

Identifiants

pubmed: 31474846
doi: 10.3389/fnbot.2019.00065
pmc: PMC6703080
doi:

Types de publication

Journal Article

Langues

eng

Pagination

65

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Auteurs

Sébastien Mick (S)

Institut de Neurosciences Cognitives et Intégratives d'Aquitaine, UMR 5287 CNRS & Univ. Bordeaux, Bordeaux, France.

Mattieu Lapeyre (M)

Pollen Robotics, Bordeaux, France.

Pierre Rouanet (P)

Pollen Robotics, Bordeaux, France.

Christophe Halgand (C)

Institut de Neurosciences Cognitives et Intégratives d'Aquitaine, UMR 5287 CNRS & Univ. Bordeaux, Bordeaux, France.

Jenny Benois-Pineau (J)

Laboratoire Bordelais de Recherche en Informatique, UMR 5800, CNRS & Univ. Bordeaux & Bordeaux INP, Talence, France.

Florent Paclet (F)

Institut de Neurosciences Cognitives et Intégratives d'Aquitaine, UMR 5287 CNRS & Univ. Bordeaux, Bordeaux, France.

Daniel Cattaert (D)

Institut de Neurosciences Cognitives et Intégratives d'Aquitaine, UMR 5287 CNRS & Univ. Bordeaux, Bordeaux, France.

Pierre-Yves Oudeyer (PY)

Inria Bordeaux Sud-Ouest, Talence, France.

Aymar de Rugy (A)

Institut de Neurosciences Cognitives et Intégratives d'Aquitaine, UMR 5287 CNRS & Univ. Bordeaux, Bordeaux, France.
Centre for Sensorimotor Performance, School of Human Movement and Nutrition Sciences, University of Queensland, Brisbane, QLD, Australia.

Classifications MeSH