Abstract
Soft robotic systems present a variety of new opportunities for solving complex problems. The use of soft robotic grippers, for example, can simplify the complexity in tasks such as the grasping of irregular and delicate objects. Adoption of soft robotics by the Informatics community and industry, however, has been slow and this is, in-part, due to the amount of hardware and software that must be developed from scratch for each use of soft system components. In this paper we detail the design, fabrication and validation of an open-source framework that we designed to lower the barrier to entry for integrating soft robotic subsystems. This framework is built on ROS (the Robot Operating System) and we use it to demonstrate a modular, soft-hard hybrid system which is capable of completing pick and place tasks. By lowering this barrier to entry through our open sourced hardware and software we hope that system designers and Informatics researchers will find it easy to integrate soft components into their existing ROS-enabled robotic systems.
Highlights
The lack of open source hardware and software for soft robotics creates a significant barrier to entry for researchers who wish to conduct research into soft robotic systems
By lowering this barrier to entry, we aim to provide the informatics community with a new opportunity to explore the benefits of soft robotics for a wide range of tasks
The open source hardware and software, which we present in this paper provide a new resource for research into integrated soft robotic systems and will lower the barrier to entry for researchers
Summary
The lack of open source hardware and software for soft robotics creates a significant barrier to entry for researchers who wish to conduct research into soft robotic systems. We detail our development of an open source, modular, soft–hard hybrid robot whose components can be manufactured and integrated into existing or robotic systems. By lowering this barrier to entry, we aim to provide the informatics community with a new opportunity to explore the benefits of soft robotics for a wide range of tasks. The established control paradigms for hard robot systems are based on assumptions that the links in an assembly are rigid, and that the joint angles can be measured using encoders. Soft robotic components do not have rigid links and so the established control methods cannot be applied (Ross et al, 2016). Soft robotics researchers require control-hardware and control-software, which is designed for their specific actuation and sensing techniques
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