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Soft modular robots have the advantages of both bionic continuum robots and modular self-reconfigurable robots. They have potential application for working in narrow space and uneven terrain. The outstanding abilities of the soft modular robots are infinite degrees of freedom and a changeable configuration. However, these advantages also incur difficulty in mathematical modeling and continuous motion control, especially for docking, which is the key to realizing a changeable configuration. Therefore, the development of a soft modular robot requires a modeling method to guide the module's motions accurately. In this paper, we design and manufacture a pneumatic soft modular robot with a novel connecting mechanism to achieve docking. A nonlinear dynamic model of our soft module is established. In particular, the analytic solutions of the module plane docking are presented. Based on the nonlinear dynamic modeling, three experiments are performed under different conditions. The experimental results pertaining to module plane bending agree with the theoretical values, which verify the accuracy of the modeling method. Moreover, fixed point docking and two modules docking experiments demonstrate the validity of the modeling method and the docking ability. The modeling method proposed in this paper can well guide the docking of soft modular robots.

The reconfigurable and modular method, and the adaptive morphology method are two main methodologies to achieve the multimodal robots. Basically, the former method mimics the biological multicellular systems, while the latter is mostly inspired by the multimodal animals. Herein inspired by the rhombic dodecahedron (RDD) origami model, a novel type of soft multicellular robots with multimodal locomotion is presented. Morphologically, the combinable and expandable three-dimensional (3D)-printed soft RDD cells are assembled into several typical patterns: in-line, cross shaped, oblong shaped, and parallelogra shaped. The kinematics based on the sequential monolithic deformations of soft RDDs is analyzed to generate multimodal locomotion: peristaltic crawling, two-anchor crawling, crawling with turning functions, and omnidirectional crawling through the propagating waves in two orthogonal directions. More encouragingly, without reorganizing the pattern or reshaping the morph, the in-line multicellular robots manifest excellent climbing abilities, where the built-in rhombic meshes alternately tighten and loosen the pole-like structures to provide the gripping forces reliably without sacrificing mobility. To wrap up, owing to the monolithic and hierarchical deformability, high reconfigurability, and 3D-printable manufacturability of the RDD, we anticipate that the soft multicellular robot can potentially manifest further contributions to the advanced robotics with embodied intelligence, such as task-oriented self-assembly robots, self-reconfigurable robotic systems, and goal-directed metamorphosis robots.

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. [ABSTRACT FROM AUTHOR]

Soft modular robots have advantages, including infinite degrees of freedom and various configurations. Most soft robots are actuated by inflating air pressure into their chambers. However, each chamber is connected to a tube that provides the air supply, which incurs drag and intertwining problems that influence the robot's motion. Moreover, the number of chambers directly affects the deformations and motion capabilities of the robot. Therefore, the crucial issue is the structure of a soft modular robot that can share an air source without reducing the number of chambers and can guarantee the deformations of the robot. In this paper, a novel mechatronics-embedded soft module was designed and manufactured, which has an air supply sharing function. Therefore, the soft modular robot can be powered via a single air tube. In addition, a wireless platform to control the air pressure of the module was built, and an experimental model was established to obtain the relationship between the deformation and pressure of the module. Four experiments were performed under different conditions. The experiments' results indicate the bending capability of the module. Moreover, hooking object, twisting motion, and bionic gesture experiments demonstrate the validity of the module's air pressure sharing function. Therefore, the air sharing supply approach proposed in this paper can be used as a reference to solve the tube drag problem of soft modular robots. [ABSTRACT FROM AUTHOR]

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.

Soft modular robots have advantages, including infinite degrees of freedom and various configurations. Most soft robots are actuated by inflating air pressure into their chambers. However, each chamber is connected to a tube that provides the air supply, which incurs drag and intertwining problems that influence the robot’s motion. Moreover, the number of chambers directly affects the deformations and motion capabilities of the robot. Therefore, the crucial issue is the structure of a soft modular robot that can share an air source without reducing the number of chambers and can guarantee the deformations of the robot. In this paper, a novel mechatronics-embedded soft module was designed and manufactured, which has an air supply sharing function. Therefore, the soft modular robot can be powered via a single air tube. In addition, a wireless platform to control the air pressure of the module was built, and an experimental model was established to obtain the relationship between the deformation and pressure of the module. Four experiments were performed under different conditions. The experiments’ results indicate the bending capability of the module. Moreover, hooking object, twisting motion, and bionic gesture experiments demonstrate the validity of the module’s air pressure sharing function. Therefore, the air sharing supply approach proposed in this paper can be used as a reference to solve the tube drag problem of soft modular robots.