270 research outputs found
Integration of Polyimide Flexible PCB Wings in Northeastern Aerobat
The principal aim of this Master's thesis is to propel the optimization of
the membrane wing structure of the Northeastern Aerobat through origami
techniques and enhancing its capacity for secure hovering within confined
spaces. Bio-inspired drones offer distinctive capabilities that pave the way
for innovative applications, encompassing wildlife monitoring, precision
agriculture, search and rescue operations, as well as the augmentation of
residential safety. The evolved noise-reduction mechanisms of birds and insects
prove advantageous for drones utilized in tasks like surveillance and wildlife
observation, ensuring operation devoid of disturbances. Traditional flying
drones equipped with rotary or fixed wings encounter notable constraints when
navigating narrow pathways. While rotary and fixed-wing systems are
conventionally harnessed for surveillance and reconnaissance, the integration
of onboard sensor suites within micro aerial vehicles (MAVs) has garnered
interest in vigilantly monitoring hazardous scenarios in residential settings.
Notwithstanding the agility and commendable fault tolerance exhibited by
systems such as quadrotors in demanding conditions, their inflexible body
structures impede collision tolerance, necessitating operational spaces free of
collisions. Recent years have witnessed an upsurge in integrating soft and
pliable materials into the design of such systems; however, the pursuit of
aerodynamic efficiency curtails the utilization of excessively flexible
materials for rotor blades or propellers. This thesis introduces a design that
integrates polyimide flexible PCBs into the wings of the Aerobat and employs
guard design incorporating feedback-driven stabilizers, enabling stable
hovering flights within Northeastern's Robotics-Inspired Study and
Experimentation (RISE) cage.Comment: 42 pages,20 figure
Optimizing the structure and movement of a robotic bat with biological kinematic synergies
In this article, we present methods to optimize the design and flight characteristics of a biologically inspired bat-like robot. In previous, work we have designed the topological structure for the wing kinematics of this robot; here we present methods to optimize the geometry of this structure, and to compute actuator trajectories such that its wingbeat pattern closely matches biological counterparts. Our approach is motivated by recent studies on biological bat flight that have shown that the salient aspects of wing motion can be accurately represented in a low-dimensional space. Although bats have over 40 degrees of freedom (DoFs), our robot possesses several biologically meaningful morphing specializations. We use principal component analysis (PCA) to characterize the two most dominant modes of biological bat flight kinematics, and we optimize our robot’s parametric kinematics to mimic these. The method yields a robot that is reduced from five degrees of actuation (DoAs) to just three, and that actively folds its wings within a wingbeat period. As a result of mimicking synergies, the robot produces an average net lift improvesment of 89% over the same robot when its wings cannot fold
Reducing Versatile Bat Wing Conformations to a 1-DoF Machine
Recent works have shown success in mimicking the flapping flight of bats on the robotic platform Bat Bot (B2). This robot has only five actuators but retains the ability to flap and fold-unfold its wings in flight. However, this bat-like robot has been unable to perform folding-unfolding of its wings within the period of a wingbeat cycle, about 100 ms. The DC motors operating the spindle mechanisms cannot attain this folding speed. Biological bats rely on this periodic folding of their wings during the upstroke of the wingbeat cycle. It reduces the moment of inertia of the wings and limits the negative lift generated during the upstroke. Thus, we consider it important to achieve wing folding during the upstroke. A mechanism was designed to couple the flapping cycle to the folding cycle of the robot. We then use biological data to further optimize the mechanism such that the kinematic synergies of the robot best match those of a biological bat. This ensures that folding is performed at the correct point in the wingbeat cycle
Describing Robotic Bat Flight with Stable Periodic Orbits
From a dynamic system point of view, bat locomotion stands out among other forms of flight. During a large part of bat wingbeat cycle the moving body is not in a static equilibrium. This is in sharp contrast to what we observe in other simpler forms of flight such as insects, which stay at their static equilibrium. Encouraged by biological examinations that have revealed bats exhibit periodic and stable limit cycles, this work demonstrates that one effective approach to stabilize articulated flying robots with bat morphology is locating feasible limit cycles for these robots; then, designing controllers that retain the closed-loop system trajectories within a bounded neighborhood of the designed periodic orbits. This control design paradigm has been evaluated in practice on a recently developed bio-inspired robot called Bat Bot (B2)
A Review of Avian-Inspired Morphing for UAV Flight Control
The impressive maneuverability demonstrated by birds has so far eluded comparably sized uncrewed aerial vehicles (UAVs). Modern studies have shown that birds’ ability to change the shape of their wings and tail in flight, known as morphing, allows birds to actively control their longitudinal and lateral flight characteristics. These advances in our understanding of avian flight paired with advances in UAV manufacturing capabilities and applications has, in part, led to a growing field of researchers studying and developing avian-inspired morphing aircraft. Because avian-inspired morphing bridges at least two distinct fields (biology and engineering), it becomes challenging to compare and contrast the current state of knowledge. Here, we have compiled and reviewed the literature on flight control and stability of avian-inspired morphing UAVs and birds to incorporate both an engineering and a biological perspective. We focused our survey on the longitudinal and lateral control provided by wing morphing (sweep, dihedral, twist, and camber) and tail morphing (incidence, spread, and rotation). In this work, we discussed each degree of freedom individually while highlighting some potential implications of coupled morphing designs. Our survey revealed that wing morphing can be used to tailor lift distributions through morphing mechanisms such as sweep, twist, and camber, and produce lateral control through asymmetric morphing mechanisms. Tail morphing contributes to pitching moment generation through tail spread and incidence, with tail rotation allowing for lateral moment control. The coupled effects of wing–tail morphing represent an emerging area of study that shows promise in maximizing the control of its morphing components. By contrasting the existing studies, we identified multiple novel avian flight control methodologies that engineering studies could validate and incorporate to enhance maneuverability. In addition, we discussed specific situations where avian-inspired UAVs can provide new insights to researchers studying bird flight. Collectively, our results serve a dual purpose: to provide testable hypotheses of flight control mechanisms that birds may use in flight as well as to support the design of highly maneuverable and multi-functional UAV designs
Optimizing the structure and movement of a robotic bat with biological kinematic synergies
In this article, we present methods to optimize the design and flight characteristics of a biologically inspired bat-like robot. In previous, work we have designed the topological structure for the wing kinematics of this robot; here we present methods to optimize the geometry of this structure, and to compute actuator trajectories such that its wingbeat pattern closely matches biological counterparts. Our approach is motivated by recent studies on biological bat flight that have shown that the salient aspects of wing motion can be accurately represented in a low-dimensional space. Although bats have over 40 degrees of freedom (DoFs), our robot possesses several biologically meaningful morphing specializations. We use principal component analysis (PCA) to characterize the two most dominant modes of biological bat flight kinematics, and we optimize our robot’s parametric kinematics to mimic these. The method yields a robot that is reduced from five degrees of actuation (DoAs) to just three, and that actively folds its wings within a wingbeat period. As a result of mimicking synergies, the robot produces an average net lift improvesment of 89% over the same robot when its wings cannot fold
Optimizing the structure and movement of a robotic bat with biological kinematic synergies
In this thesis we present methods to optimize the design and flight characteristics of a biologically-inspired bat-like robot. Recent work has designed the topological structure for the wing kinematics of this robot; here we present methods to optimize the geometry of this structure, and to compute actuator trajectories that yield successful flight behaviors. Our approach is motivated by recent studies on biological bat flight, which have shown that the salient aspects of wing motion can be accurately represented in a low-dimensional space. We use principal components analysis (PCA) to characterize the dominant modes of biological bat flight kinematics, and optimize our robotic design to mimic these. In particular, we use the first and second principal components to shape the parametric kinematics and actuator trajectories through finite state nonlinear constrained optimization. The method yields a robot mechanism that, despite having only five degrees of actuation, possesses several biologically meaningful morphing specializations. We have validated our approach in both simulation and flight experiments with our prototype robotic bat
IMPROVED PREDICTION OF FLAPPING WING AERIAL VEHICLE PERFORMANCE THROUGH COMPONENT INTERACTION MODELING
Flapping wing aerial vehicles offer the promise of versatile performance, however prediction of flapping wing aerial vehicle performance is a challenging task because of complex interconnectedness in vehicle functionality. To address this challenge, performance is estimated by using component-level modeling as a foundation. Experimental characterization of the drive motors, battery, and wings is performed to identify important functional characteristics and enable selection of appropriate modeling techniques. Component-level models are then generated that capture the performance of each vehicle component. Validation of each component-level model shows where errors are eliminated by capturing important dynamic functionality. System-level modeling is then performed by creating linkages between component-level models that have already been individually validated through experimental testing, leading to real-world functional constraints that are realized and correctly modeled at the system level. The result of this methodology is a system-level performance prediction that offers the ability to explore the effects of changing vehicle components as well as changing functional properties, while maintaining computational tractability. Simulated results are compared to experimental flight test data collected with an instrumented flapping wing aerial vehicle, and are shown to offer good accuracy in estimation of system-level performance properties
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