Quantifying the Leaping Motion Using a Self-Propelled Bionic Robotic Dolphin Platform

Leger J, Goldbogen JA. Spin-leap performance by cetaceans is influenced by moment of inertia

Cetaceans are capable of extraordinary locomotor behaviors in both water and air. Whales and dolphins can execute aerial leaps by swimming rapidly to the water surface to achieve an escape velocity. Previous research on spinner dolphins demonstrated the capability of leaping and completing multiple spins around their longitudinal axis with high angular velocities. This prior research suggested the slender body morphology of spinner dolphins together with the shapes and positions of their appendages allowed for rapid spins in the air. To test whether greater moments of inertia reduced spinning performance, videos and biologging data of cetaceans above and below the water surface were obtained. The principal factors affecting the number of aerial spins a cetacean can execute were moment of inertia and use of control surfaces for subsurface corkscrewing. For spinner dolphin, Pacific striped dolphin, bottlenose dolphin, minke whale and humpback whale, each with swim speeds of 6-7 m s-1, our model predicted that the number of aerial spins executable was 7, 2, 2, 0.76 and 1, respectively, which was consistent with observations. These data implied that the rate of subsurface corkscrewing was limited to 14.0, 6.8, 6.2, 2.2 and 0.75 rad s-1 for spinner dolphins, striped dolphins, bottlenose dolphins, minke whales and humpback whales, respectively. In our study, the moment of inertia of the cetaceans spanned a 21,000-fold range. The greater moments of inertia for the last four species produced large torques on control surfaces that limited subsurface corkscrewing motion and aerial maneuvers compared with spinner dolphins.

Target-Following Control of a Biomimetic Autonomous System Based on Predictive Reinforcement Learning

Biological fish often swim in a schooling manner, the mechanism of which comes from the fact that these schooling movements can improve the fishes' hydrodynamic efficiency. Inspired by this phenomenon, a target-following control framework for a biomimetic autonomous system is proposed in this paper. Firstly, a following motion model is established based on the mechanism of fish schooling swimming, in which the follower robotic fish keeps a certain distance and orientation from the leader robotic fish. Second, by incorporating a predictive concept into reinforcement learning, a predictive deep deterministic policy gradient-following controller is provided with the normalized state space, action space, reward, and prediction design. It can avoid overshoot to a certain extent. A nonlinear model predictive controller is designed and can be selected for the follower robotic fish, together with the predictive reinforcement learning. Finally, extensive simulations are conducted, including the fix point and dynamic target following for single robotic fish, as well as cooperative following with the leader robotic fish. The obtained results indicate the effectiveness of the proposed methods, providing a valuable sight for the cooperative control of underwater robots to explore the ocean.

A Circular Formation Method for Biomimetic Robotic Fish Inspired by Fish Milling

Circular motion phenomena, akin to fish milling, are prevalent within the animal kingdom. This paper delineates two fundamental mechanisms underlying such occurrences: forward following and circular topological communication. Leveraging these pivotal concepts, we present a multi-agent formation circular model based on a second-order integrator. This model engenders the attainment of homogeneous intelligence convergence along the circumferential trajectory. The convergence characteristics are intricately linked to the number of agents and the model parameters. Consequently, we propose positive and negative solutions for ascertaining the convergent circle property and model parameters. Furthermore, by integrating our proposed formation control methodology with a robotic fish dynamics model, we have successfully implemented simulations and experiments, demonstrating the circular formation of multiple biomimetic robotic fish. This study provides a mathematical explication for the circular motion observed in animal groups and introduces a novel approach to achieving circular formation in multiple robots inspired by biological phenomena.

Performance Optimization for Bionic Robotic Dolphin with Active Variable Stiffness Control

Aquatic animals such as fish and cetaceans can actively modulate their body stiffness with muscle to achieve excellent swimming performance under different situations. However, it is still challenging for a robotic swimmer with bionic propulsion mode to dynamically adjust its body stiffness to improve the swimming speed due to the difficulties in designing an effective stiffness adjustment structure. In this paper, based on the special torque mode of a motor, we propose an active variable stiffness control method for a robotic dolphin to pursue better swimming speed. Different from a variable stiffness structure design, a torque control strategy for the caudal motor is employed to imitate the physical property of a torsion spring to act as the variable stiffness component. In addition, we also establish a dynamic model with the Lagrangian method to explore the variable stiffness mechanism. Extensive experiments have validated the dynamic model, and then the relationships between frequency and stiffness on swimming performance are presented. More importantly, through integrating the dynamic model and torque actuation mode-based variable stiffness mechanism, the online performance optimization scheme can be easily realized, providing valuable guidance in coordinating system parameters. Finally, experiments have demonstrated the stiffness adjustment capability of the caudal joint, validating the effectiveness of the proposed control method. The results also reveal that stiffness plays an essential role in swimming motion, and the active stiffness adjustment can significantly contribute to performance improvement in both speed and efficiency. Namely, with the adjustment of stiffness, the maximum speed of our robotic dolphin achieves up to 1.12 body length per second (BL/s) at 2.88 Hz increasing by 0.44 BL/s. Additionally, the efficiency is also improved by 37%. The conducted works will offer some new insights into the stiffness adjustment of robotic swimmers for better swimming performance.

Platform development and gliding optimization of a robotic flying fish with morphing pectoral fins

The aquatic-aerial robot with the free interface crossing can enhance adaptability in complex aquatic environments. However, its design is extremely challenging for the striking discrepancies in propulsion principles. The flying fish in nature exhibits remarkable multi-modal cross-domain locomotion capability, such as high-maneuvers swimming, agile water-air crossing, and long-distance gliding, providing extensive inspiration. In this paper, we present a unique aquatic-aerial robotic flying fish with powerful propulsion and a pair of morphing wing-like pectoral fins to realize cross-domain motion. Furthermore, to explore the gliding mechanism of flying fish, a dynamic model with a morphing structure of pectoral fins is established, and a double deep Q-network-based control strategy is proposed to optimize the gliding distance. Finally, experiments were conducted to analyze the locomotion of the robotic flying fish. The results suggest that the robotic flying fish can successfully perform the 'fish leaping and wing spreading' cross-domain locomotion with an exiting speed of 1.55 m s^-1(5.9 body lengths per second, BL/s) and a crossing time of 0.233 s indicating its great potential in cross-domain. Simulation results have validated the effectiveness of the proposed control strategy and indicated that the dynamical adjustment of morphing pectoral fins contributes to improving the gliding distance. The maximum gliding distance has increased by 7.2%. This study will offer some significant insights into the system design and performance optimization of aquatic-aerial robots.