An Interconnected Soft Modular Robot with Locomotive Modules and Flexible Structures Actuated Through a Single Method

This article presents a unique soft robot comprised of highly compliant locomotive modules interconnected with jamming-capable flexible envelopes. The modules incorporate origami-inspired actuators and suction cups for robust omnidirectional locomotion, acting as collective elements that drive the system's movement and control. The flexible envelopes enable dynamic interactions with the environment through stiffness modulation via granular jamming. A unified pneumatic actuation system consolidates all robot functions, simplifying the mechanical architecture. The system's capabilities are demonstrated through shape formation, object grasping and transportation, obstacle navigation, and diverse terrain locomotion experiments, highlighting its adaptability and cooperative nature. Furthermore, a simulation-based design optimization approach using a genetic algorithm enhances the system's grasping performance by exploring the different module and envelope configurations. The interconnected soft robot system represents a unique fusion of highly compliant modules and bodies, advancing modular soft robotics for effective environmental interactions.

Inspired by the growth behavior of plants: biomimetic soft robots that just meet the requirements of use

Soft robots are usually manufactured using the pouring method and can only be configured with a fixed execution area, which often faces the problem of insufficient or wasteful performance in real-world applications, and cannot be reused for other tasks. In order to overcome this limitation, we propose a simple and controllable rather than redesigned method inspired by the bionic growth behavior of plants, and prepare bionic soft robots that can just meet the requirements of use, and transform biological intelligence into mechanical intelligence. Based on finite element method, we establish a theoretical model of soft robot performance. And the experimental platform is designed to conduct experimental research on the prototype of the soft robot. Compared with the results obtained through the theoretical model, it is found out that the experimental bending angle and elongation are slightly smaller than the simulation results. (The maximum error of elongation prediction for soft robots (Fashion 1-4) is 5.7%, 5.9%, 6%, and 6%, and the maximum error of bending angle prediction is 7.1%, 7.5%, 7.6%, and 7.6%, respectively). The high consistence between our theoretical model and the experimental results shows that the theoretical model is applicable to accurately predict the performance of soft robots. It is worth pointing out that this design as proposed in this paper can be extended to the wider field of soft robotics as a generic one.

A self-organizing robotic aggregate using solid and liquid-like collective states

Designing robotic systems that can change their physical form factor as well as their compliance to adapt to environmental constraints remains a major conceptual and technical challenge. To address this, we introduce the Granulobot, a modular system that blurs the distinction between soft, modular, and swarm robotics. The system consists of gear-like units that each contain a single actuator such that units can self-assemble into larger, granular aggregates using magnetic coupling. These aggregates can reconfigure dynamically and also split into subsystems that might later recombine. Aggregates can self-organize into collective states with solid- and liquid-like properties, thus displaying widely differing compliance. These states can be perturbed locally via actuators or externally via mechanical feedback from the environment to produce adaptive shape-shifting in a decentralized manner. This, in turn, can generate locomotion strategies adapted to different conditions. Aggregates can move over obstacles without using external sensors or coordinates to maintain a steady gait over different surfaces without electronic communication among units. The modular design highlights a physical, morphological form of control that advances the development of resilient robotic systems with the ability to morph and adapt to different functions and conditions.