A Computational Fluid Dynamics (CFD) Analysis of an Undulatory Mechanical Fin Driven by Shape Memory Alloy

Many fishes use undulatory fin to propel themselves in the underwater environment. These locomotor mechanisms have a popular interest to many researchers. In the present study, we perform a three-dimensional unsteady computation of an undulatory mechanical fin that is driven by Shape Memory Alloy （SMA）. The objective of the computation is to investigate the fluid dynamics of force production associated with the undulatory mechanical fin. An unstructured, grid-based, unsteady Navier-Stokes solver with automatic adaptive remeshing is used to compute the unsteady flow around the fin through five complete cycles. The pressure distribution on fin surface is computed and integrated to provide fin forces which are decomposed into lift and thrust. The velocity field is also computed throughout the swimming cycle. Finally, a comparison is conducted to reveal the dynamics of force generation according to the kinematic parameters of the undulatory fin （amplitude, frequency and wavelength）.

Locomotion and Depth Control of Robotic Fish with Modular Undulating Fins

This paper presents an environmental-friendly robotic system mimicking the undulating fins of a fish.To mimic the actual flexible fin of real fish,a fin-like mechanism with a series of connecting linkages is modeled and attached to the robotic fish,by virtue of a specially designed strip.Each link is able to turn and slide with respect to the adjacent link.These driving linkages are then used to form a mechanical fin consisting of several fin segments,which are able to produce undulations,similar to those produced by the actual fish fins.Owing to the modular and re-configurable design of the mechanical fin,we are able to construct biomimetic robotic fish with various swimming modes by fin undulations.Some qualitative and workspace observations by experiments of the robotic fish are shown and discussed.

Bio-inspired Flow Sensing and Prediction for Fish-like Undulating Locomotion： A CFD-aided Approach

Feedback flow information is of significance to enable underwater locomotion controllers with higher adaptability and efficiency within varying environments. Inspired from fish sensing their external flow via near-body pressure, a computational scheme is proposed and developed in this paper. In conjunction with the scheme, Computational Fluid Dynamics （CFD） is employed to study the bio-inspired fish swimming hydrodynamics. The spatial distribution and temporal variation of the near-body pressure of fish are studied over the whole computational domain. Furthermore, a filtering algorithm is designed and implemented to fuse near-body pressure of one or multiple points for the estimation on the external flow. The simulation results demonstrate that the proposed computational scheme and its corresponding algorithm are both effective to predict the inlet flow velocity by using near-body pressure at distributed spatial points.

A Three-Dimensional Kinematics Analysis of a Koi Carp Pectoral Fin by Digital Image Processing

Pectoral fins fascinate researchers for their important role in fish maneuvers. By possessing a complicated flexible structure with several fin rays made by a thin film, the fin exhibits a three-dimensional （3D） motion. The complex 3D fin kinematics makes it challenging to study the performance of pectoral fin. Nevertheless, a detailed study on the 3D motion pattern of pectoral fins is necessary to the design and control ofa bio-inspired fin rays. Therefore, a highspeed photography system is introduced in this paper to study the 3D motion ofa Koi Carp by analyzing the two views of its pectoral fin simultaneously. The key motions of the pectoral fins are first captured in both hovering and retreating. Next, the 3D configuration of the pectoral fins is recon- structed by digital image processing, in which the movement of fin rays during fish retreating and hovering is obtained. Fur- thermore, the method of Singular Value Decomposition （SVD） is adopted to extract the basic motion patterns of pectoral fins from extensive image sequences, i.e. expansion, bending, cupping, and undulation. It is believed that the movement of the fin rays and the basic patterns of the pectoral fins obtained in the present work can provide a good foundation for the development and control of bionic flexible pectoral fins for underwater propeller.

Tactical conflict resolution in urban airspace for unmanned aerial vehicles operations using attention-based deep reinforcement learning

Unmanned aerial vehicles(UAVs)have gained much attention from academic and industrial areas due to the significant number of potential applications in urban airspace.A traffic management system for these UAVs is needed to manage this future traffic.Tactical conflict resolution for unmanned aerial systems(UASs)is an essential piece of the puzzle for the future UAS Traffic Management(UTM),especially in very low-level(VLL)urban airspace.Unlike conflict resolution in higher altitude airspace,the dense high-rise buildings are an essential source of potential conflict to be considered in VLL urban airspace.In this paper,we propose an attention-based deep reinforcement learning approach to solve the tactical conflict resolution problem.Specifically,we formulate this task as a sequential decision-making problem using Markov Decision Process(MDP).The double deep Q network(DDQN)framework is used as a learning framework for the host drone to learn to output conflict-free maneuvers at each time step.We use the attention mechanism to model the individual neighbor's effect on the host drone,endowing the learned conflict resolution policy to be adapted to an arbitrary number of neighboring drones.Lastly,we build a simulation environment with various scenarios covering different types of encounters to evaluate the proposed approach.The simulation results demonstrate that our proposed algorithm provides a reliable solution to minimize secondary conflict counts compared to learning and non-learning-based approaches under different traffic density scenarios.

Gait Study and Pattern Generation of a Starfish-Like Soft Robot with Flexible Rays Actuated by SMAs

This paper presents the design and development of a starfish-like soft robot with flexible rays and the implementation of multi-gait locomotion using Shape Memory Alloy （SMA） actuators. The design principle was inspired by the starfish, which possesses a remarkable symmetrical structure and soft internal skeleton. A soft robot body was constructed by using 3D printing technology. A kinematic model of the SMA spring was built and developed for motion control according to displacement and force requirements. The locomotion inspired from starfish was applied to the implementation of the multi-ray robot through the flexible actuation induced multi-gait movements in various environments. By virtue of the proposed ray control patterns in gait transition, the soft robot was able to cross over an obstacle approximately twice of its body height. Results also showed that the speed of the soft robot was 6.5 times faster on sand than on a clammy rough terrain. These experiments demonstrated that the bionic soft robot with flexible rays actuated by SMAs and multi-gait locomotion in proposed patterns can perform successfully and smoothly in various terrains.

On-line Optimization of Biomimetic Undulatory Swimming by an Experiment-based Approach

An experiment-based approach is proposed to improve the performance of biomimetic undulatory locomotion through on-line optimization. The approach is implemented through two steps： （1） the generation of coordinated swimming gaits by artificial Central Pattern Generators （CPGs）; （2） an on-line searching of optimal parameter sets for the CPG model using Genetic Algorithm （GA）. The effectiveness of the approach is demonstrated in the optimization of swimming speed and energy effi- ciency for a biomimetic fin propulsor. To evaluate how well the input energy is converted into the kinetic energy of the pro- pulsor, an energy-efficiency index is presented and utilized as a feedback to regulate the on-line searching with a closed-loop swimming control. Experiments were conducted on propulsor prototypes with different fin segments and the optimal swimming patterns were found separately. Comparisons of results show that the optimal curvature of undulatory propulsor, which might have different shapes depending on the actual prototype design and control scheme. It is also found that the propulsor with six fin segments, is preferable because of hizher speed and lower energy efficiency.

Multiple air route crossing waypoints optimization via artificial potential field method

Air route crossing waypoint optimization is one of the effective ways to improve airspace utilization,capacity and resilience in dealing with air traffic congestion and delay.However,research is lacking on the optimization of multiple Crossing Waypoints(CWPs)in the fragmented airspace separated by Prohibited,Restricted and Dangerous areas(PRDs).To tackle this issue,this paper proposes an Artificial Potential Field(APF)model considering attractive forces produced by the optimal routes and repulsive forces generated by obstacles.An optimization framework based on the APF model is proposed to optimize the different airspace topologies varying the number of CWPs,air route segments and PRDs.Based on the framework,an adaptive method is developed to dynamically control the optimization process in minimizing the total air route cost.The proposed model is applied to a busy controlled airspace.And the obtained results show that after optimization the safety-related indicators:conflict number and controller workload reduced by 7.75%and 6.51%respectively.As for the cost-effectiveness indicators:total route length,total air route cost and non-linear coefficient,declined by 1.74%,3.13%and 1.70%respectively.While the predictability indicator,total flight delay,saw a notable reduction by 7.96%.The proposed framework and methodology can also provide an insight in the understanding of the optimization to other network systems.