Modular self-reconfigurable robots (MSRRs) have significantly progressed in hardware and algorithm development. However, they are generally used in terrestrial environments, leaving broad scenarios to be explored and benefited. This letter presents a novel amphibious self-reconfigurable robot (ASRR) that combines the flexibility of modular robots with the environmental adaptability characteristic of amphibious robots. We customize the structure and circuitry to ensure the prototype functions effectively in both aquatic and terrestrial environments. Our design specifically addresses the challenge of module sealing, with a detailed description of the structure provided. A multi-functional connecting face is proposed for coupling, power sharing, sensing, and configuration identification, using only electro-permanent magnets (EPMs) without increasing the mechanical complexity. These functionalities are scalable based on the number of modules and enable the integration of independent modules into an overall system. The module's cubic structure features two rotational degrees of freedom (DOFs) and four connecting faces, similar to a universal joint. The results show the excellent performance and similar capabilities of this MSRR system across various environments. Notably, the buoyancy offsets some of the effects of gravity and significantly enhances the modules' capacity to manipulate additional modules.

The theoretical capability of modular robots to organize the overall robot into different structures with different functions has broad prospects in space exploration. Therefore, a novel modular space robot named Space Module is developed, and a self‐assembly strategy inspired by biological cooperative and mutual assistance behaviors is proposed. First, the meta‐module method is utilized to endow nonmobile modules with the mobility. Second, the mutual assistance is presented to achieve position and posture reachability of the assembly unit while minimizing the effect of meta‐modules on granularity. Then, according to the unique motion characteristics of the meta‐module and mutual assistance, an assembly planner is designed to obtain the assembly sequences to realize the self‐manufacturing of desired configurations. Finally, the validity and feasibility of the proposed assembly strategy are further confirmed by demonstrations. An interactive preprint version of the article can be found here: https://doi.org/10.22541/au.167264888.81237462/v1.

Research on modular robots for space exploration has primarily focused on reconfiguration, with limited attention given to the maneuverability in space environment, which is essential for harnessing the advantages of reconfiguration. In this paper, a modular snake-like robot (MSR) is designed, which is expected to emulate a snake to navigate complex environments and employ the reconfiguration capability for on-site shape-shifting. To this end, a snake-like motion analysis and planning method is proposed for MSR. Firstly, we explore the feasibility of utilizing modules in realizing snake-like motion, including functional compatibility and structural constraints. Secondly, we analyze the kinematics of MSR and design joint coordination motion schemes to meet the requirements of snake-like motion. Finally, a path planning method based on reinforcement learning is proposed, which fully considers the motion characteristics and the structural constraints. Through motion analysis and planning, a balance between environmental adaptability and versatility can be achieved. Simulations of comparisons and potential applications further demonstrate the significant advantages of MSR in space exploration.

Modular robots have unique advantages in handling faults and improving their robustness due to their self‐reconfiguration capacity and homogeneous interchangeability. When locked joint failure occurs in modular robots, the distribution of the failed modules will affect the manipulation capacity of the robot. In this article, a novel self‐reconfiguration method that utilizes only the remaining resources available to mitigate the damage caused by module joint failures is proposed. The key node configuration is searched by the particle swarm optimization (PSO) algorithm, and then the collision‐free reconfiguration path is planned by the rapidly exploring random trees (RRT) algorithm. The proposed method not only handles single‐module lockup failure but can also be expanded to multi‐module lockup failures, fully improving the fault tolerance of the modular robot. The method is deployed on the hardware, and the feasibility of the algorithm is verified by self‐reconfiguration experiments containing faulty modules.