Search

Birds' flight characteristics such as gliding and dynamic soaring have inspired various optimizations and designs of wind turbines. The implementation of biological wing geometries such as the airfoil profile of seabirds has improved wind turbine performance. However, the field can still benefit from further investigation into the aerodynamic characteristics of an inspired design. Therefore, this study evaluated the effect of a seagull airfoil design on the aerodynamic performance of the National Renewable Energy Laboratory (NREL) Phase VI wind turbine. By replacing its S809 airfoil with the laser-scanned profile of the seagull airfoil, the aerodynamic behavior at key locations of the NREL Phase VI wind turbine blade was numerically simulated in a three-dimensional environment using the Ansys Fluent 2022 R1 computational fluid dynamics (CFD) code. The results were validated against the experimental data, and analysis of the torque outputs, pressure distributions, and velocity profiles that were generated by both the baseline and modified models demonstrated the ability of the seagull airfoil profile to modify regions of minimum and maximum local velocities to achieve highly favorable pressure differentials, significantly increasing the torque output of the NREL Phase VI wind turbine by 350, 539, 823, and 577 Nm at 10, 15, 20, and 25 m/s inlet velocities, respectively. [ABSTRACT FROM AUTHOR]

Aerodynamic noise emitted by small wind turbines is a concern due to their proximity to urban environments. Broadband airfoil self-noise has been found to be the major source, and several studies have discussed techniques to reduce airfoil leading-edge and trailing-edge noises. Reduction mechanisms inspired by owl wings and their airfoil sections were found to be most effective. However, their effect/s on the tip vortex noise remain underexplored. Therefore, this paper investigates the effects of implementing an owl airfoil design on the tip vortex noise generated by the National Renewable Energy Laboratory (NREL) Phase VI wind turbine to gain an understanding of the relationship, if any, between airfoil design and the tip vortex noise mechanism. Numerical prediction of aeroacoustics is employed using the Ansys Fluent Broadband Noise Sources function for airfoil self-noise radiation. Detailed comparisons and evaluations of the generated acoustic power levels (APLs) for two distinguished inlet velocities were made with no loss in torque. Although the owl airfoil design increased the maximum generated APL by the baseline model from 105 dB to 110 dB at the lower inlet velocity, it significantly reduced the surface area generating the noise, and reduced the maximum APL generated by the baseline model by 4 dB as the inlet velocity increased. The ability of the owl airfoil to mitigate the velocity effects along the span of the blade was found to be its main noise reduction mechanism. [ABSTRACT FROM AUTHOR]

To improve the rapidity of path planning for drones in unknown environments, a new bio-inspired path planning method using E-DQN (event-based deep Q-network), referring to introducing event stream to reinforcement learning network, is proposed. Firstly, event data are collected through an airsim simulator for environmental perception, and an auto-encoder is presented to extract data features and generate event weights. Then, event weights are input into DQN (deep Q-network) to choose the action of the next step. Finally, simulation and verification experiments are conducted in a virtual obstacle environment built with an unreal engine and airsim. The experiment results show that the proposed algorithm is adaptable for drones to find the goal in unknown environments and can improve the rapidity of path planning compared with that of commonly used methods. [ABSTRACT FROM AUTHOR]

Birds’ flight characteristics such as gliding and dynamic soaring have inspired various optimizations and designs of wind turbines. The implementation of biological wing geometries such as the airfoil profile of seabirds has improved wind turbine performance. However, the field can still benefit from further investigation into the aerodynamic characteristics of an inspired design. Therefore, this study evaluated the effect of a seagull airfoil design on the aerodynamic performance of the National Renewable Energy Laboratory (NREL) Phase VI wind turbine. By replacing its S809 airfoil with the laser-scanned profile of the seagull airfoil, the aerodynamic behavior at key locations of the NREL Phase VI wind turbine blade was numerically simulated in a three-dimensional environment using the Ansys Fluent 2022 R1 computational fluid dynamics (CFD) code. The results were validated against the experimental data, and analysis of the torque outputs, pressure distributions, and velocity profiles that were generated by both the baseline and modified models demonstrated the ability of the seagull airfoil profile to modify regions of minimum and maximum local velocities to achieve highly favorable pressure differentials, significantly increasing the torque output of the NREL Phase VI wind turbine by 350, 539, 823, and 577 Nm at 10, 15, 20, and 25 m/s inlet velocities, respectively.

Aerodynamic noise emitted by small wind turbines is a concern due to their proximity to urban environments. Broadband airfoil self-noise has been found to be the major source, and several studies have discussed techniques to reduce airfoil leading-edge and trailing-edge noises. Reduction mechanisms inspired by owl wings and their airfoil sections were found to be most effective. However, their effect/s on the tip vortex noise remain underexplored. Therefore, this paper investigates the effects of implementing an owl airfoil design on the tip vortex noise generated by the National Renewable Energy Laboratory (NREL) Phase VI wind turbine to gain an understanding of the relationship, if any, between airfoil design and the tip vortex noise mechanism. Numerical prediction of aeroacoustics is employed using the Ansys Fluent Broadband Noise Sources function for airfoil self-noise radiation. Detailed comparisons and evaluations of the generated acoustic power levels (APLs) for two distinguished inlet velocities were made with no loss in torque. Although the owl airfoil design increased the maximum generated APL by the baseline model from 105 dB to 110 dB at the lower inlet velocity, it significantly reduced the surface area generating the noise, and reduced the maximum APL generated by the baseline model by 4 dB as the inlet velocity increased. The ability of the owl airfoil to mitigate the velocity effects along the span of the blade was found to be its main noise reduction mechanism.

To improve the rapidity of path planning for drones in unknown environments, a new bio-inspired path planning method using E-DQN (event-based deep Q-network), referring to introducing event stream to reinforcement learning network, is proposed. Firstly, event data are collected through an airsim simulator for environmental perception, and an auto-encoder is presented to extract data features and generate event weights. Then, event weights are input into DQN (deep Q-network) to choose the action of the next step. Finally, simulation and verification experiments are conducted in a virtual obstacle environment built with an unreal engine and airsim. The experiment results show that the proposed algorithm is adaptable for drones to find the goal in unknown environments and can improve the rapidity of path planning compared with that of commonly used methods.

Design of legged robots is still an open problem with several implementation challenges and there is little material available to guide new designs. Moreover, usually the actuator sets of the robot are heavy and bulky and are placed near the joints, which increases the weight and inertia of the legs and consequently results in instability, slower movement and high energy consumption. This paper presents the design, modeling, and control of the Guará, a sixteen-degree-of-freedom (DOF) legged robot, covering all stages of development of a quadruped robot, including experiments with a prototype. The system is composed by four legs, each one with 4 DOF. To reduce the leg’s weight and inertia, here we present a design concept for the legs where the actuators are positioned on the robot platform and timing belt transmissions are used to drive the joints. Moreover, the design of the legs mimics the human leg by presenting the knees faced forward and its locomotion pattern mimics the quadruped wave gait. With this configuration, the robot is able to walk on straight lines or free curved paths. The control system of the robot consists of a high-level state machine and a lower level PID position controller. The electronics are embedded over a flat platform coupled to the legs. The kinematics of the robot was studied and an integrated environment was provided for walking simulation, adjustment, and diagnosis of operation. The experimental results are focused on the kinematics of the legs and the stability of the robot and show a good agreement between the designed and executed movements. This paper is presented as a framework that can be generalized to other systems and can be a useful reference for the design of other legged robots.

We model an artificial root which grows in the soil for underground prospecting. Its evolution is described by a controlled system of two integro-partial differential equations: one for the growth of the body and the other for the elongation of the tip. At any given time, the angular velocity of the root is obtained by solving a minimization problem with state constraints. We prove the existence of solutions to the evolution problem, up to the first time where a "breakdown configuration" is reached. Some numerical simulations are performed to test the effectiveness of our feedback control algorithm. [ABSTRACT FROM AUTHOR]

Design of legged robots is still an open problem with several implementation challenges and there is little material available to guide new designs. Moreover, usually the actuator sets of the robot are heavy and bulky and are placed near the joints, which increases the weight and inertia of the legs and consequently results in instability, slower movement and high energy consumption. This paper presents the design, modeling, and control of the Guará, a sixteen-degree-of-freedom (DOF) legged robot, covering all stages of development of a quadruped robot, including experiments with a prototype. The system is composed by four legs, each one with 4 DOF. To reduce the leg's weight and inertia, here we present a design concept for the legs where the actuators are positioned on the robot platform and timing belt transmissions are used to drive the joints. Moreover, the design of the legs mimics the human leg by presenting the knees faced forward and its locomotion pattern mimics the quadruped wave gait. With this configuration, the robot is able to walk on straight lines or free curved paths. The control system of the robot consists of a highlevel state machine and a lower level PID position controller. The electronics are embedded over a flat platform coupled to the legs. The kinematics of the robot was studied and an integrated environment was provided for walking simulation, adjustment, and diagnosis of operation. The experimental results are focused on the kinematics of the legs and the stability of the robot and show a good agreement between the designed and executed movements. This paper is presented as a framework that can be generalized to other systems and can be a useful reference for the design of other legged robots. [ABSTRACT FROM AUTHOR]

Nature is a great source of inspirations for solving complex computational problems. The inspirations can come from any source like some theory of physics or chemistry, a mathematical concept or from the biological world. Several biologically inspired techniques are implemented in various areas of research and development. These technologies can be grouped into two broad segments: Evolutionary and Swarm based depending on the nature of inspiration. This paper presents an overview of these biologically inspired techniques and its various implementations for traffic optimization with an objective to optimize congestion, minimize wait time, improve safety and reduce pollution. [ABSTRACT FROM AUTHOR]

Polyurethane elastomers have been widely used in aerospace engineering, intelligent electronics, smart buildings, and other high-tech fields. However, preparing polyurethane elastomers with self-healing at room temperature, high toughness, and strength, remains a significant challenge. Hence, inspired by human muscles, A room-temperature self-healing and recyclable polyurethane elastomer was developed. This elastomer possesses tough, high strength, and good elastic recoverability by adjusting the structure of its hard domains. In detail, the obtained polyurethane elastomers exhibit a high tensile strength of 30.3 MPa, an elongation at break of 1114.6 %, toughness of 126.4 MJ/m3, fracture energy of 96.4 kJ/m2, and remarkable anti-fatigue properties as demonstrated by cyclic tensile. Meanwhile, the introduction of asymmetric aliphatic ring structure into the hard domain structure is beneficial for accelerating the exchange rate of dynamic bonds in polyurethane elastomers, resulting in a healing efficiency is up to 90.8 %. In addition, the mechanical properties of the resultant polyurethane elastomers are not lost after being recycled three times. Finally, the polyurethane elastomer is used as the substrate for electromagnetic shielding material, and the electromagnetic shielding efficiency was investigated. This study demonstrates the design of self-healing elastomers at room temperature with high toughness and strength, which provides a new avenue for the development of sustainable electronic materials in the future. [Display omitted] [ABSTRACT FROM AUTHOR]

Many drone platforms have matured to become nearly optimal flying machines with only modest improvements in efficiency possible. “Chimera” craft combine fixed wing and rotary wing characteristics while being substantially less efficient than both. The increasing presence of chimeras suggests that their mix of vertical takeoff, hover, and more efficient cruise is invaluable to many end users. We discuss the opportunity for flapping wing drones inspired by large insects to perform these mixed missions. Dragonflies particularly are capable of efficiency in all modes of flight. We will explore the fundamental principles of dragonfly flight to allow for a comparison between proposed flapping wing technological solutions and a flapping wing organism. We chart one approach to achieving the next step in drone technology through systems theory and an appreciation of how biomimetics can be applied. New findings in dynamics of flapping, practical actuation technology, wing design, and flight control are presented and connected. We show that a theoretical understanding of flight systems and an appreciation of the detail of biological implementations may be key to achieving an outcome that matches the performance of natural systems. We assert that an optimal flapping wing drone, capable of efficiency in all modes of flight with high performance upon demand, might look somewhat like an abstract dragonfly.

The actuated abdomens of insects such as dragonflies have long been suggested to play a role in optimisation and control of flight. We have examined the effect of this type of actuation in the simplified case of a small fixed wing aircraft to determine whether energetic advantages exist in normal flight when compared to the cost of actuation using aerodynamic control surfaces. We explore the benefits the abdomen/tail might provide to balance level flight against trim changes. We also consider the transient advantage of using alternative longitudinal control effectors in a pull up flight maneuver. Results show that the articulated abdomen significantly reduces energy consumption and increase performance in isolated manoeuvres. The results also indicate a design feature that could be incorporated into small unmanned aircraft under particular circumstances. We aim to highlight behaviours that would increase flight efficiency to inform designers of micro aerial vehicles and to aid the analysis of insect flight behaviour and energetics.

This paper proposes the design of a bipedal robotic controller where the function between the sensory input and motor output is treated as a black box derived from human data. In order to achieve this, we investigated the causal relationship between ground contact information from the feet and leg muscle activity n human walking and calculated filter functions which transform sensory signals to motor actions. A minimal, nonlinear, and robust control system was created and subsequently analysed by applying it to our bipedal robot RunBot III without any central pattern generators or precise trajectory control. The results demonstrate that our controller can generate stable robotic walking. This indicates that complex locomotion patterns can result from a simple model based on reflexes and supports the premise that human-derived control strategies have potential applications in robotics or assistive devices. [ABSTRACT FROM AUTHOR]

Smooth-backboned “continuum” robot structures offer novel ways to create robot shapes and movements. In this paper, we show how circumnutation, a motion strategy commonly employed by plants, can be implemented and usefully exploited with continuum robots. We discuss how the kinematics of circumnutation, which combines local backbone growth with periodic backbone bending, can be created using extensible continuum robot hardware. The underlying kinematics are generated by adapting kinematic models of plant growth. We illustrate the effectiveness of that approach with experimental results with a tendril-like robot exploring a congested environment.

The human mind is a complex biological member with unique abilities. Today, even the most advanced computers cannot do all the brain's calculations in one second. The mind is teachable, and its logic will change based on what it has learned over time. This behavior will be the base of a theory presented in this article, named Incomprehensible but Intelligible-in-time (IbI) Logics. From a mental point of view and according to human knowledge, what it has not learned is a non-logic. However, this may change through time. Meanwhile, the IbI logic is a non-logic that may become an obvious logic in the future. This article has been formed to introduce a side of science to identify IbI logic and organize the mind's scientific idioms. Based on the introduced theory, a new optimization algorithm called IbI Logics Algorithm (ILA) was also presented and compared with some other algorithms. The performance of the proposed algorithm in several constrained and unconstrained examples were evaluated. The results showed the acceptable performance and potential of the ILA for optimization goals. [ABSTRACT FROM AUTHOR]

• The inspire–mapping–synthesis bioinspired design paradigm for mechanism design. • The concept and composition of the bioinspired parallel driving mechanism (PDM). • A bionic 5-DOF (3T2R) PDM inspired by the manual two-arm operation. • A new blocking strategy is proposed to match the driving mechanism for the PDM. Biological inspiration is a critical approach for the innovative design of mechanisms. This paper presents the concept of the inspire–mapping–synthesis design process as a paradigm for biological inspiration in the mechanism design. By establishing the mapping relationships from the organism's local musculoskeletal system to the mechanism configuration, a new type of mechanism called parallel driving mechanism (PDM) is proposed. The PDM consists of the driving mechanism, operating mechanism, and connecting joint. On this basis, a bionic 5-DOF PDM inspired by the manual two-arm operation is synthesized. First, the operating mechanism is designed under the guidance of a graphical type synthesis method. The two-parallelogram composite structure and the coupling chain in the operating mechanism bring better stiffness. Then a blocking strategy is proposed to match the driving mechanism. Finally, the motion mechanism is revealed to perform the inverse kinematic position analysis. The proposed 5-DOF PDM has good potential in terms of high accuracy and high stiffness manipulation. This work provides new ideas for innovative mechanism design. [ABSTRACT FROM AUTHOR]

Combining model-based and model-free reinforcement learning systems in robotic cognitive architectures appears as a promising direction to endow artificial agents with flexibility and decisional autonomy close to mammals. In particular, it could enable robots to build an internal model of the environment, plan within it in response to detected environmental changes, and avoid the cost and time of planning when the stability of the environment is recognized as enabling habit learning. However, previously proposed criteria for the coordination of these two learning systems do not scale up to the large, partial and uncertain models autonomously learned by robots. Here we precisely analyze the performances of these two systems in an asynchronous robotic simulation of a cube-pushing task requiring a permanent trade-off between speed and accuracy. We propose solutions to make learning successful in these conditions. We finally discuss possible criteria for their efficient coordination within robotic cognitive architectures. [ABSTRACT FROM AUTHOR]

People have always tried to understand natural phenomena. In computer science natural phenomena are mostly used as a source of inspiration for solving various problems in distributed systems such as optimization, clustering, and data processing. In this paper we will give an overview of research in field of computer science where fireflies in nature are used as role models for time synchronization. We will compare two models of oscillators that explain firefly synchronization along with other phenomena of synchrony in nature (e.g., synchronization of pacemaker cells of the heart and synchronization of neuron networks of the circadian pacemaker). Afterwards, we will present Mirollo and Strogatz׳s pulse coupled oscillator model together with its limitations. As discussed by the authors of the model, this model lacks of explanation what happens when oscillators are nonidentical. It also does not support mobile and faulty oscillators. Finally, it does not take into consideration that in communication among oscillators there are communication delays. Since these limitations prevent Mirollo and Strogatz׳s model to be used in real-world environments (such as Machine-to-Machine systems), we will sum up related work in which scholars investigated how to modify the model in order for it to be applicable in distributed systems. However, one has to bear in mind that there are usually large differences between mathematical models in theory and their implementation in practice. Therefore, we give an overview of both mathematical models and mechanisms in distributed systems that were designed after them. [ABSTRACT FROM AUTHOR]

There is an increasing interest in conceiving robotic systems that are able to move and act in an unstructured and not predefined environment, for which autonomy and adaptability are crucial features. In nature, animals are autonomous biological systems, which often serve as bio-inspiration models, not only for their physical and mechanical properties, but also their control structures that enable adaptability and autonomy-for which learning is (at least) partially responsible. This work proposes a system which seeks to enable a quadruped robot to online learn to detect and to avoid stumbling on an obstacle in its path. The detection relies in a forward internal model that estimates the robot's perceptive information by exploring the locomotion repetitive nature. The system adapts the locomotion in order to place the robot optimally before attempting to step over the obstacle, avoiding any stumbling. Locomotion adaptation is achieved by changing control parameters of a central pattern generator (CPG)-based locomotion controller. The mechanism learns the necessary alterations to the stride length in order to adapt the locomotion by changing the required CPG parameter. Both learning tasks occur online and together define a sensorimotor map, which enables the robot to learn to step over the obstacle in its path. Simulation results show the feasibility of the proposed approach. [ABSTRACT FROM AUTHOR]

Understanding and adapting the underlying principles of biological systems to engineering systems have the promise of enabling many new mechatronic systems that can operate in unstructured and uncertain environments robustly and efficiently. This paper first reports a brief survey of recent studies on bio-inspired mechatronic systems and their biological counterparts in respects of locomotion, actuation, sensing, and control. Next, brief highlights of the 20 papers in this “Focused Section on Bio-Inspired Mechatronics” are given. Finally, current challenges and future trends of bio-inspired mechatronic systems are described. [ABSTRACT FROM PUBLISHER]