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Automatic Generation of Locomotion Patterns for Soft Modular Reconfigurable Robots

Xin Sui, Hegao Cai, Dongyang Bie, Yu Zhang, Jie Zhao, Yanhe Zhu

Year
2019
Citations
37
Access
Open access

Abstract

In recent years, soft modular robots have become popular among researchers with the development of soft robotics. However, the absence of a visual 3D simulation platform for soft modular robots hold back the development of the field. The three-dimensional simulation platform plays an important role in the field of multi-body robots. It can shorten the design cycle, reduce costs, and verify the effectiveness of the optimization algorithm expediently. Equally importantly, evolutionary computation is a very effective method for designing the controller of multi-body robots and soft robots with hyper redundancy and large parametric design space. In this paper, a tradeoff between the structural complexity of the soft modular robot and computational power of the simulation software is made. A reconfigurable soft modular robot is designed, and the open-source simulation software VOXCAD is re-developed to simulate the actual soft robot. The evolutionary algorithm is also applied to search for the most efficient motion pattern for an established configuration in VOXCAD, and experiments are conducted to validate the results.

Keywords

Modular designSelf-reconfiguring modular robotRobotComputer scienceRedundancy (engineering)SoftwareComputationControl engineeringSoft roboticsParametric statistics

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