Bionic amphibious robots are the intersection of biology and robotics; they have the advantages of environmental adaptability and maneuverability. An amphibious robot that combines walking and swimming move modes inspired by a crab (Portunus) is presented in this article. The outstanding characteristic of the robot is that its environmental adaptability relies on the bionic multi-modal movement, which is based on two modular bionic swimming legs and six modular walking legs. We designed the biomimetic crab robot based on the biological observation results. The design, analysis, and simulation of its structure and motion parameters are introduced in this paper. The swimming propulsion capability and the walking performance are verified through indoor, pool, and seaside experiments. In conclusion, the designed bionic crab robot provides a platform with practical application capabilities in amphibious environment detection, concealed reconnaissance, and aquaculture.

Amphibious environments formed from sand and water present a formidable challenge to the running motion of field robots, as the mixing of granular media (GM) and water makes the force laws of robotic legs more complicated during robot running. To this end, we extended the granular resistive force theory (RFT) to saturated wet granular media, named saturated granular RFT (SGRFT), which can be suitable for saturated wet sand submerged in water. This method can extend RFT for dry GM to saturated wet granular media (SWGM) by using the method’s velocity and depth coefficient. The force laws of the robotic legs in dry GM and SWGM were tested, compared, and analyzed. The difference in force laws between the two kinds of media, from the sensitivity to speed (10 mm/s~50 mm/s) and depth (0~60 mm), was calculated. More than 70% of the prediction results of the horizontal resistive force using SGRFT have an error of less than 6%. The effectiveness of the SGRFT in legged robots is proved by simulation and testing of three kinds of legs. The difference in force laws when running is proved by the experiments of the robot equipped with the propeller-leg in dry GM and SWGM, which is vital for amphibious robots working in shoal environments (including dry GM and SWGM ground).

Accurate joint dynamics models are essential for the compliance and robustness of robot control, especially for robots operating in complex underwater environments. To improve the precision of joint dynamics models, much research focuses on refining specific parameters or incorporating previously overlooked parameters through theoretical deductions and simulations. However, the effectiveness of these advancements can only be determined through empirical validation using the new model. This letter delineates a methodology that facilitates the assessment of potential avenues for enhancing the model, without necessitating prior theoretical derivation. Specifically, a methodology based on stochastic extension is proposed for evaluating directions of model improvement, applied to enhancing the LuGre model for underwater sealed joints. This approach employs the coefficient of variation in LuGre model parameters to assess the direction of model enhancement, with the comparison of coefficients of variation before and after improvement elucidating the superiority of the enhancements. Experimental outcomes corroborate that the LuGre model, refined using this evaluative technique, can precisely estimate friction forces across diverse typical conditions in underwater joint applications. The sealed joints utilizing the improved model demonstrated enhanced response times and precision in underwater environments.