Zhengxing Wu

Fish can actively modulate the mechanical properties of their muscles to adapt to complex hydrodynamic environments, and extensive research has been dedicated to replicating such adaptive locomotion capabilities in bionic robotic fish. Unlike the widely investigated variable-stiffness tail designs in existing studies, this paper proposes a decoupled tunable rotational inertia mechanism for the robotic fish caudal peduncle, which enables independent regulation of tail rotational inertia without altering the global center of mass of the robot. A symmetric cable-driven transmission system equipped with a pair of oppositely moving mass spheres is adopted to realize real-time online inertia tuning while sustaining the robot’s dynamic balance. A high-fidelity fluid-structure interaction (FSI) dynamic model is established by integrating the pseudo rigid body method (PRBM) and the boundary data immersion method (BDIM). Simulation and experimental results demonstrate that rotational inertia modulation exerts a significant regulatory effect on the swimming performance of bionic robotic fish. Specifically, increased rotational inertia enhances thrust generation and forward swimming velocity within a specific tail-beat frequency range, whereas it degrades locomotion performance when the tail-beat frequency exceeds a critical threshold. Remarkably, the performance improvement enabled by enhanced rotational inertia can only be achieved via internal mass redistribution. In contrast, directly attaching additional mass to increase rotational inertia will almost invariably impair the swimming capability of the robot. This study reveals the unique regulatory effect of rotational inertia as an independent control input for bio-inspired underwater robots, providing a unique regulatory effect for the development of unified impedance-inertia adaptive control frameworks for future bionic underwater platforms.

Achieving cross-medium locomotion remains a longstanding challenge in the field of bionic robotic fish. Current locomotion strategies often fail to enable effective aerial motion after water exit, primarily due to limitations in propulsion performance. To address this, we propose a novel cross-medium approach inspired by the taxiing behavior of flying fish. To validate this strategy, we developed a lightweight, high-speed robotic fish that integrates an electromechanical coupling drive system and a compliant passive joint. Based on the Lagrangian method, we established a kinetic model for the taxiing motion to investigate how passive joint stiffness and driving frequency influence taxiing performance. Extensive simulation and experimental results demonstrate that surface propulsion performance can be effectively enhanced by tuning passive joint stiffness to match driving frequency and intrinsic frequency to enter a resonant state. This enables the robotic fish to achieve a successful transition to taxiing motion at the resonant frequency, with a stable speed of 1.74 m/s (equivalent to 6.78 body lengths per second) and a lower Cost of Transport. These findings provide valuable insights for the design and optimization of robotic fish with passive joints and offer a promising pathway to realizing efficient cross-medium locomotion.

Biomimetic underwater platforms serve as critical instrumentation for water quality monitoring and environmental sensing applications, where optimized motion trajectories and energy management directly impact measurement coverage and data acquisition quality. This paper addresses the trajectory optimization challenges for underwater exploration platforms in sensing missions, proposing a novel approach to enhance measurement efficiency and extend operational endurance. First, a motion-constraint-based path planning framework is developed, generating global path with initial directional decision using the A* algorithm and employing iterative linear quadratic regulator (iLQR) with piecewise sampling smoothing for local obstacle avoidance. Additionally, an offline optimization framework is designed to optimize flexible tail stiffness parameters, thereby reducing energy consumption and extending measurement mission duration. For path following, a nonlinear model predictive control (NMPC)-based strategy is introduced, achieving precise measurement position tracking through head yaw angle smoothing and line-of-sight navigation to improve data acquisition ability. Finally, numerical simulations validate the effectiveness of the proposed methods, significantly enhancing the measurement capability of biomimetic underwater exploration platforms in practical environmental monitoring applications.

Penguins exhibit remarkable swimming capabilities with high speeds and efficient gliding for extended durations, thus providing an exemplary biological model for biomimetic underwater vehicles. In this article, inspired by the flapping–gliding locomotion mechanism observed in aquatic organisms, we create a novel robotic penguin capable of multimodal locomotion that combines biomimetic flapping and efficient gliding motions. Initially, a pair of three-degree-of-freedom (3-DOF) wings and a 1-DOF vertical tail is constructed to generate forward thrust and steering torque for biomimetic flapping motion. Meanwhile, a buoyancy adjustment system and a slider system are designed for gliding motion. Thereafter, a full-state dynamic model, including both flapping and gliding motions, is established by employing the Newton–Euler method. Particularly, the hydrodynamic coefficients are precisely calibrated through system identification utilizing experimental data. Finally, extensive simulations and experiments are conducted, encompassing forward swimming and turning maneuvers in both flapping and gliding modes. The results obtained validate the superior flapping and gliding performance of the designed system as well as the effectiveness of the dynamic model, providing new insights for next-generation underwater vehicles with enhanced maneuverability in dynamic and complex aquatic environments.

Biological adhesion represents a remarkable evolutionary adaptation, as exemplified by remoras using dorsal suction cups for hitchhiking and octopuses employing independently controllable suction cups to adhere to complex surfaces. Therefore, this study focuses on the design, quantitative analysis, and system-level construction of their artificial counterparts. Firstly, a reversible, low preload requirement, and multi-sensory suction cup array is fabricated and mounted on the dorsal of a bionic robotic fish. Notably, each channel of the suction cup array is independently controlled to enhance adaptability. Subsequently, five metrics are proposed to systematically measure and analyze the adhesion system. Specifically, the optimal structural parameters enable the miniaturized suction cup to achieve a pull-off force of 16 N on an acrylic plane, with the capability to adapt to varying surface radius and roughness. Furthermore, by leveraging sensory information and a hierarchical control strategy, we develop an autonomous adhesion method that enables the robotic fish to fine-tune the adhesion system according to varying surface characteristics and dynamically adjust under disturbed conditions. Finally, various aquatic experiments are conducted to validate the effectiveness and adaptability of the proposed adhesion system.