Vlimb: A Wire-Driven Wearable Robot for Bodily Extension, Balancing Powerfulness and Reachability Shogo Sawaguchi 1, Temma Suzuki 1, Akihiro Miki 1, Kento Kawaharazuka 1, Sota Y uzaki 1, Shunnosuke Y oshimura 1, Y oshimoto Ribayashi 1, Kei Okada 1, Masayuki Inaba 1 Abstract -- Numerous wearable robots have been developed to meet the demands of physical assistance and entertainment. These wearable robots range from body-enhancing types that assist human arms and legs to body-extending types that have extra arms. This study focuses specifically on wearable robots of the latter category, aimed at bodily extension. However, they have not yet achieved the level of powerfulness and reachability equivalent to that of human limbs, limiting their application to entertainment and manipulation tasks involving lightweight objects. Therefore, in this study, we develop an body-extending wearable robot, Vlimb, which has enough powerfulness to lift a human and can perform manipulation. Leveraging the advantages of tendon-driven mechanisms, Vlimb incorporates a wire routing mechanism capable of accommodating both delicate manipulations and robust lifting tasks. Moreover, by introducing a passive ring structure to overcome the limited reachability inherent in tendon-driven mechanisms, Vlimb achieves both the powerfulness and reachability comparable to that of humans. This paper outlines the design methodology of Vlimb, conducts preliminary manipulation and lifting tasks, and verifies its effectiveness.

For robots to become more versatile and expand their areas of application, their bodies need to be suitable for contact with the environment. When the human body comes into contact with the environment, it is possible for it to continue to move even if the positional relationship between muscles or the shape of the muscles changes. We have already focused on the effect of geometric deformation of muscles and proposed a drive system called wire-wound Muscle-Tendon Complex (ww-MTC), an extension of the wire drive system. Our previous study using a robot with a two-dimensional configuration demonstrated several advantages: reduced wire loosening, interference, and wear; improved robustness during environmental contact; and a muscular appearance. However, this design had some problems, such as excessive muscle expansion that hindered inter-muscle movement, and confinement to planar motion. In this study, we develop the ww-MTC into a three-dimensional shape. We present a fundamental construction method for a muscle exterior that expands gently and can be contacted over its entire surface. We also apply the three-dimensional ww-MTC to a 2-axis 3-muscle robot, and confirm that the robot can continue to move while adapting to its environment.

Quadruped robots that individual researchers can build by themselves are crucial for expanding the scope of research due to their high scalability and customizability. These robots must be easily ordered and assembled through e-commerce or DIY methods, have a low number of components for easy maintenance, and possess durability to withstand experiments in diverse environments. Various quadruped robots have been developed so far, but most robots that can be built by research institutions are relatively small and made of plastic using 3D printers. These robots cannot withstand experiments in external environments such as mountain trails or rubble, and they will easily break with intense movements. Although there is the advantage of being able to print parts by yourself, the large number of components makes replacing broken parts and maintenance very cumbersome. Therefore, in this study, we develop a metal quadruped robot MEVIUS, that can be constructed and assembled using only materials ordered through e-commerce. We have considered the minimum set of components required for a quadruped robot, employing metal machining, sheet metal welding, and off-the-shelf components only. Also, we have achieved a simple circuit and software configuration. Considering the communication delay due to its simple configuration, we experimentally demonstrate that MEVIUS, utilizing reinforcement learning and Sim2Real, can traverse diverse rough terrains and withstand outside experiments. All hardware and software components can be obtained from https://github.com/haraduka/mevius.