期刊
INTERNATIONAL JOURNAL OF ADVANCED ROBOTIC SYSTEMS
卷 14, 期 2, 页码 -出版社
SAGE PUBLICATIONS INC
DOI: 10.1177/1729881416687132
关键词
Assistive robotics; soft robotics; machine learning; robot control
类别
资金
- People Programme (Marie Curie Actions) of the European Union's Seventh Framework Programme [FP7/2007-2013]
- REA [608022]
- European Commission through the I-SUPPORT project [643666]
- Italian Ministry of Foreign Affairs
- General Directorate for the Promotion of the Country System
- Bilateral and Multilateral Scientific and Technological Cooperation Unit
- Joint Laboratory on Biorobotics Engineering project
Manipulators based on soft robotic technologies exhibit compliance and dexterity which ensures safe human-robot interaction. This article is a novel attempt at exploiting these desirable properties to develop a manipulator for an assistive application, in particular, a shower arm to assist the elderly in the bathing task. The overall vision for the soft manipulator is to concatenate three modules in a serial manner such that (i) the proximal segment is made up of cable-based actuation to compensate for gravitational effects and (ii) the central and distal segments are made up of hybrid actuation to autonomously reach delicate body parts to perform the main tasks related to bathing. The role of the latter modules is crucial to the application of the system in the bathing task; however, it is a nontrivial challenge to develop a robust and controllable hybrid actuated system with advanced manipulation capabilities and hence, the focus of this article. We first introduce our design and experimentally characterize its functionalities, which include elongation, shortening, omnidirectional bending. Next, we propose a control concept capable of solving the inverse kinetics problem using multiagent reinforcement learning to exploit these functionalities despite high dimensionality and redundancy. We demonstrate the effectiveness of the design and control of this module by demonstrating an open-loop task space control where it successfully moves through an asymmetric 3-D trajectory sampled at 12 points with an average reaching accuracy of 0.79 cm +/- 0.18 cm. Our quantitative experimental results present a promising step toward the development of the soft manipulator eventually contributing to the advancement of soft robotics.
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