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Soft robotics is an emerging technology that provides robots with the ability to adapt to the environment and safely interact with it. Here, the ability of these robots to identify the surface of interaction is critical for grasping and locomotion tasks. This paper describes the capability of a four-limb soft robot that can identify background materials through the collection of reflection coefficients using an embedded antenna and machine learning techniques. The material of a soft-limb robot was characterized in terms of the relative permittivity and the loss tangent for the design of an antenna to collect reflection coefficients. A slot antenna was designed and embedded into a soft limb in order to extract five features in reflection coefficients including the resonant frequency, −3 dB bandwidth taken from the lowest S11, the value of the lowest S11, −3 dB bandwidth taken from the highest S11, and the number of resonant frequencies. A soft robot with the embedded antenna was tested on nine different background materials in an attempt to identify surrounding terrain information and a better robotic operation. The tested background materials included concrete, fabric, grass, gravel, metal, mulch, soil, water, and wood. The results showed that the robot was capable of distinguishing among the nine different materials with an average accuracy of 93.3% for the nine background materials using a bagged decision-tree-based ensemble method algorithm.

 

Abstract The deformability of soft material robots provides them with the ability to transform between complex shapes and forms. This unique ability facilitates Modular Soft Robots (MSoRos) to assemble and reconfigure into different configurations, e.g., planar and spherical. These topologies display widely different locomotion modes that are desirable to navigate different environments, e.g., crawling or rolling for these cases. This research presents topology design and optimization methodology of MSoRos capable of both homogeneous and heterogeneous reconfiguration in spherical and planar configurations. Homogeneous reconfiguration refers to the scenario when all the modules are identical, while the heterogeneous contains nonidentical modules. The sequential design approach uses a polyhedron (Archimedean or Platonic) as the base solid to define module characteristics. As the design processes involve nonlinear projections, the base polyhedron also dictates the type of reconfiguration—heterogeneous (Archimedean) or homogeneous (Platonic). Thereafter, it applies the polyhedron vertex alignment principle to ensure geometric alignment of the modules during reconfiguration. Planar and spherical distortion metrics are defined to quantify distortions due to reconfiguration. Subsequently, the optimal topology is obtained by minimizing a cost function that is a weighted sum of the two distortion metrics. The result is a set of MSoRos capable of distinct 1D and 2D planar configurations (both heterogeneous and homogeneous) and multiple 3D spherical configurations of varying radii (both heterogeneous and homogeneous). The methodology is validated on a MSoRo system based on the combination of a cuboctahedron (Archimedean solid) and a cube and an octahedron (Platonic solids). 

Robustness, compactness, and portability of tensegrity robots make them suitable candidates for locomotion on unknown terrains. Despite these advantages, challenges remain relating to simplicity of fabrication and locomotion. The paper introduces a design solution for fabricating tensegrity robots of varying morphologies with modular components created using rapid prototyping techniques, including 3D printing and laser-cutting. % It explores different robot morphologies that attempt to balance structural complexity while facilitating smooth locomotion. The techniques are utilized to fabricate simple tensegrity structures, followed by tensegrity robots in icosahedron and half-circle arc morphologies. Locomotion strategies for such robots involve altering of the position of center-of-mass to induce `tip-over'. Furthermore, the design of curved links of tensegrity mechanisms facilitates continuous change in the point of contact (along the curve) as compared to piece-wise continuous in the traditional straight links (point contact) which induces impulse reaction forces during locomotion. The resulting two tensegrity robots - six-straight strut icosahedron and two half-circle arc morphology - achieve locomotion through internal mass-shifting utilizing the presented modular mass-shifting mechanism. The curve-link tensegrity robot demonstrates smooth locomotion along with folding-unfolding capability.