Most flapping-wing aircraft wings use a single degree of freedom to generate lift and thrust by flapping up and down,while relying on the tail control surfaces to manage attitude.However,these aircraft have certain limitations,such as poor accuracy in attitude control and inadequate roll control capabilities.This paper presents a design for an active torsional mechanism at the wing's trailing edge,which enables differential variations in the pitch angle of the left and right wings during flapping.This simple mechanical form significantly enhances the aircraft's roll control capacity.The experimental verification of this mechanism was conducted in a wind tunnel using the RoboEagle flapping-wing aerial vehicle that we developed.The study investigated the effects of the control strategy on lift,thrust,and roll moment during flapping flight.Additionally,the impact of roll control on roll moment was examined under various wind speeds,flapping frequencies,angles of attack,and wing flexibility.Furthermore,several rolling maneuver flight tests were performed to evaluate the agility of RoboEagle,utilizing both the elevon control strategy and the new roll control strategy.The results demonstrated that the new roll control strat-egy effectively enhances the roll control capability,thereby improving the attitude control capabilities of the flapping-wing aircraft in complex wind field environments.This conclusion is supported by a comparison of the control time,maximum roll angle,average roll angular velocity,and other relevant parameters between the two control strategies under identical roll control input.

Flapping-wing rotor(FWR)is an innovative bio-inspired micro aerial vehicle capable of vertical take-off and landing.This unique design combines active flapping motion and passive wing rotation around a vertical central shaft to enhance aerody-namic performance.The research on FWR,though relatively new,has contributed to 6％of core journal publications in the micro aerial vehicle field over the past two decades.This paper presents the first comprehensive review of FWR,analysing the current state of the art,key advances,challenges,and future research directions.The review highlights FWR's distinctive kinematics and aerodynamic superiority compared to traditional flapping wings,fixed wings,and rotary wings,discuss-ing recent breakthroughs in efficient,passive wing pitching and asymmetric stroke amplitude for lift enhancement.Recent experiments and remote-controlled take-off and hovering tests of single and dual-motor FWR models have showcased their effectiveness.The review compares FWR flight performance with well-developed insect-like flapping-wing micro aerial vehicles as the technology readiness level progresses from laboratory to outdoor flight testing,advancing from the initial flight of a 2.6 g prototype to the current free flight of a 60-gram model.The review also presents ongoing research in bionic flexible wing structures,flight stability and control,and transitioning between hovering and cruise flight modes for an FWR,setting the stage for potential applications.

Legged robots show great potential for high-dynamic motions in continuous interaction with the physical environment,yet achieving animal-like agility remains significant challenges.Legged animals usually predict and plan their next locomotion by combining high-dimensional information from proprioception and exteroception,and adjust the stiffness of the body's skeletal muscle system to adapt to the current environment.Traditional control methods have limitations in handling high-dimensional state information or complex robot motion that are difficult to plan manually,and Deep Reinforcement Learn-ing(DRL)algorithms provide new solutions to robot motioncontrol problems.Inspired by biomimetics theory,we propose a perception-driven high-dynamic jump adaptive learning algorithm by combining DRL algorithms with Virtual Model Control(VMC)method.The robot will be fully trained in simulation to explore its motion potential by learning the factors related to continuous jumping while knowing its real-time jumping height.The policy trained in simulation is successfully deployed on the bio-inspired single-legged robot testing platform without further adjustments.Experimental results show that the robot can achieve continuous and ideal vertical jumping motion through simple training

目的:对设计的6RSS仿人并联咀嚼机器人进行刚性动力学建模分析.方法:首先,推导刚性动力学建模所需的运动变量(包括平动/转动速度和加速度)函数.其次,使用牛顿-欧拉法则建立机器人的刚性动力学模型.最后,在机器人受到咀嚼反力情况下,跟踪口腔健康志愿者的咀嚼运动轨迹,并开展数值计算.结果:数值计算结果表明,机器人的驱动力矩和约束力出现峰值的时刻和咀嚼反力出现峰值的时刻一致.结论:外力对机器人的逆动力学有较大影响,该研究为机器人的运动控制以及优化设计提供了理论依据.

Inspired by the driving muscles of the human arm,a 4-Degree of Freedom(DOF)concentrated driving humanoid robotic arm is proposed based on a spatial double parallel four-bar mechanism.The four-bar mechanism design reduces the inertia of the elbow-driving unit and the torque by 76.65％and 57.81％,respectively.Mimicking the human pose regulation strategy that the human arm picks up a heavy object by adjusting its posture naturally without complicated control,the robotic arm features an integrated position-level closed-form inverse solution method considering both geometric and load capacity limitations.This method consists of a geometric constraint model incorporating the arm angle(φ)and the Global Configuration(GC)to avoid joint limits and singularities,and a load capacity model to constrain the feasible domain of the arm angle.Further,trajectory tracking simulations and experiments are conducted to validate the feasibility of the proposed inverse solution method.The simulated maximum output torque,maximum output power and total energy consumption of the robotic arm are reduced by up to 2.0％,13.3％,and 33.3％,respectively.The experimental results demonstrate that the robotic arm can bear heavy loads in a human-like posture,effectively reducing the maximum output torque and energy consumption of the robotic arm by 1.83％and 5.03％,respectively,while avoiding joints beyond geometric and load capacity limitations.The proposed design provides a high payload-weight ratio and an efficient pose control solution for robotic arms,which can potentially broaden the application spectrum of humanoid robots.

Lizards use the synergy between their feet and tail to climb on slopes and vertical terrains.They use their soft adhesive feet with millions of small hairs to increase their contact area with the terrain surface and press their tails against the terrain to actively maintain stability during climbing.Inspired by this,we propose a bio-inspired climbing robot based on a new approach wherein the synergy between soft feet and an active tail with a soft adhesive tip allows the robot to climb stably on even and uneven terrains at different slope angles.We evaluate and compare the climbing performance of the robot on three different terrains(hard,soft,and fluffy)at different slope angles.Various robot configurations are employed,including those with standard hard feet and soft feet in combination with an active tail—with and without a soft tip.The experimental results show that the robot having soft feet and a tail with the soft tip achieves the best climbing performance on all ter-rains,with maximum climbing slopes of 40°,45°,and 50° on fluffy,soft,and hard terrains,respectively.Its payload capacity depends on the type of terrain and the inclination angle.Moreover,our robot performs multi-terrain transitions(climbing from horizontal to sloped terrains)on three different terrains of a slope.This approach can allow a climbing robot to walk and climb on different terrains,extending the operational range of the robot to areas with complex terrains and slopes,e.g.,in inspection,exploration,and construction.

生物中枢模式发生器(CPG)对六足机器人的步态控制具有重大研究意义,为此提出一种基于Kimura神经元振荡器的六足机器人CPG步态控制方法.首先,以蜘蛛为仿生对象设计六足机器人机械结构并对其进行运动学解算;然后,基于Kimura神经元振荡器建立振荡器模型并对其参数整定;其次,针对机器人6条单腿的相位关系设计CPG网络模型;最后,通过计算机仿真工具和样机进行联合实验.结果表明,基于Kimura神经元振荡器生成的CPG网络模型输出信号幅值和相位差稳定,能够满足六足机器人步态控制需求,为六足机器人的步态控制提供一种可行性方案.

Lightweight structures are widely used across different industry sectors.However,they get easily excited by external influ-ences,such as vibrations.Undesired high vibration amplitudes can be avoided by shifting the structural eigenfrequencies,which can be achieved adapting the structural design considering optimisation procedures and structures primarily inspired by diatoms.This procedures has been applied to the development process of a girder structure installed in a synchrotron radiation facility to support heavy magnets and other components.The objective was to design a 2.9 m long girder structure with high eigenfrequencies,a high stiffness and a low mass.Based on a topology optimisation result,a parametric beam-shell model including biologically inspired structures(e.g.,Voronoi combs,ribs,and soft and organic-looking transitions)was built up.The subsequent cross-sectional optimisation using evolutionary strategic optimisation revealed an optimum girder structure,which was successfully manufactured using the casting technology.Eigenfrequency measurements validated the numerical models.Future changes in the specifications can be implemented in the bio-inspired development process to obtain adapted girder structures.

Moth Flame Optimization(MFO)is a nature-inspired optimization algorithm,based on the principle of navigation technique of moth toward moon.Due to less parameter and easy implementation,MFO is used in various field to solve optimization problems.Further,for the complex higher dimensional problems,MFO is unable to make a good trade-off between global and local search.To overcome these drawbacks of MFO,in this work,an enhanced MFO,namely WF-MFO,is introduced to solve higher dimensional optimization problems.For a more optimal balance between global and local search,the original MFO's exploration ability is improved by an exploration operator,namely,Weibull flight distribution.In addition,the local optimal solutions have been avoided and the convergence speed has been increased using a Fibonacci search process-based technique that improves the quality of the solutions found.Twenty-nine benchmark functions of varying complexity with 1000 and 2000 dimensions have been utilized to verify the projected WF-MFO.Numerous popular algorithms and MFO versions have been compared to the achieved results.In addition,the robustness of the proposed WF-MFO method has been evaluated using the Friedman rank test,the Wilcoxon rank test,and convergence analysis.Compared to other methods,the proposed WF-MFO algorithm provides higher quality solutions and converges more quickly,as shown by the experiments.Furthermore,the proposed WF-MFO has been used to the solution of two engineering design issues,with striking success.The improved performance of the proposed WF-MFO algorithm for addressing larger dimensional optimization problems is guaranteed by analyses of numerical data,statistical tests,and convergence performance.

The water snail Pomacea canaliculata retracts the discoidal and multi-layered operculum to protect the soft body from being attacked by predators,and releases it when threats lifted.However,the duration of the operculum retraction is usually less than that of the operculum protraction.In this paper,we elucidate the biological compliant mechanism of the operculum.By using confocal laser scanning microscopy,we find that the operculum has compliant sandwiched layers between hard layers.The layered structure results in a compliant mechanism with a bidirectional stiffness for the locking and unlocking processes of the operculum.A mathematical model is derived to rationalize the bidirectional stiffness mechanism of the operculum.In addition,we carry out the experiments on the locking and unlocking processes.The experimental results show that the locking tension is about two-fifths of the unlocking tension of the operculum.Moreover,based on the mechanical proper-ties of the operculum with the layered structure,we designed an operculum-inspired structure,which may have a variety of potential applications in combined driving patterns.