Underactuated robots often require involved routines for trajectory planning due to their complex dynamics. Flapping-wing aerial vehicles have unsteady aerodynamics and periodic gaits that complicate the planning procedure. In this paper, we improve upon existing methods for flight planning by introducing a two-stage optimization routine to plan flapping flight trajectories. The first stage solves a trajectory optimization problem with a data-driven fixed-wing approximation model trained with experimental flight data. The solution to this is used as the initial guess for a second stage optimization using a flapping-wing model trained with the same flight data. We demonstrate the effectiveness of this approach with a bat robot in both simulation and experimental flight results. The speed of convergence, the dependency on the initial guess, and the quality of the solution are improved, and the robot is able to track the optimized trajectory of a dive maneuver.

Bat flight has been an underdeveloped area of bio-inspired robotics because of the vast complexities of biological bat flight and the over 40 degrees of freedom present in their bodies. The robotic flapping system Bat Bot (B2) has been shown to exhibit fundamental properties of biological bat flight with its articulated wings, its deformable membrane, and its controllable hindlimbs. However, the system is limited in performance by its relatively large mass for the thrust it produces. In an effort to further pursue this important area of flapping flight, we have made several important hardware improvements to the system based on biological inspiration. These include passive wrist joints to reduce negative lift in the upstroke and a novel elastic fiber membrane to mimic the anistropic nature of bat skin for performance and durability. The redesigned flapping mechanism and structure have reduced the weight by 22%, increased the flapping amplitude, lowered mechanical slackness, and improved mass distribution. These hardware improvements are functional together in free-flight tests. This new system Bat Bot 2.0 (B2.0) provides insights into the important elements of design of bat robots, and it brings the goal of complex bat flight maneuvers closer to reality.

Flapping wing aerial vehicles rely heavily on accurate models for a variety of different tasks.There have been significant efforts in creating both analytical and data-driven models for many of these types of vehicles including ornithopters and small aerial vehicles mimicking insects.However, very few works have explored modeling for aerial vehicles with a skeletal structure throughout the wings and a single flexible membrane that covers the wings and tail such as is found in robots with bat morphology.In this paper, we build upon previous efforts to model a bat robot using a combination of first-principles and data-driven tools.We record a series of load cell tests and freeflight experiments, and we optimize the model parameters to improve long-term flight prediction.We introduce several extra terms in the model including a term explaining the coupling between wings and tail in order to maximize the effectiveness of collected flight data.The result is a model that performs well in prediction for a range of different tail actuator configurations as demonstrated by our flight results using a bat robot.

Planning flight trajectories is important for practical application of flying systems. This topic has been well studied for fixed and rotary winged aerial vehicles, but far fewer works have explored it for flapping systems. Bat Bot (B2) is a bio-inspired flying robot that mimics bat flight, and it possesses the ability to follow a designed trajectory with its on-board electronics and sensing. However, B2's periodic flapping and its complex aerodynamics present major challenges in modeling and planning feasible flight paths. In this paper, we present a generalized approach that uses a model with direct collocation methods to plan dynamically feasible flight maneuvers. The model is made to be both accurate through collection of load cell force data for parameter selection and computationally inexpensive such that it can be used efficiently in a nonlinear solver. We compute the trajectory of launching B2 to a desired altitude and a banked turn maneuver, and we validate our methods with experimental flight results of tracking the launch trajectory with a PD controller.

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.

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.

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).

We have developed an unattended sensor for detecting anomalous radiation sources. The system combines several technologies to reduce size and weight, increase battery lifetime, and improve decision-making capabilities. Sixteen Cs2LiYCl6:Ce (CLYC) scintillators allow for gamma-ray spectroscopy and neutron detection in the same volume. Low-power electronics for readout, high voltage bias, and digital processing reduce the total operating power to 1.7 W. Computationally efficient analysis algorithms perform spectral anomaly detection and isotope identification. When an alarm occurs, the system transmits alarm information over a cellular modem. In this paper, we describe the overall design of the unattended sensor, present characterization results, and compare the performance to stock NaI:Tl and He-3 detectors.

The sophisticated and intricate connection between bat morphology and flight capabilities makes it challenging to employ conventional flying robots to replicate the aerial locomotion of these creatures.In recent work, a bat inspired soft Micro Aerial Vehicle (MAV) called Bat Bot (B2) with five Degrees of Actuation (DoA) has been constructed to mimic the flight behavior of a biological bat.Major differences in structural topology resulted from this simpler kinematic complexity, and thus it is necessary to find the dimensions of B2's structure and the behavior of its actuators such that the wingbeat cycle of B2 closely mimics that of a biological bat.The current work assumes the previously designed structure of B2 and presents a synergistic design approach to imitate the kinematic synergies of a biological bat.Recent findings have unveiled that the most dominant synergies in a biological bat could be combined to accurately represent the original kinematic movement, therefore simplifying its dimensional complexity.In this work, Principal Component Analysis (PCA) has been employed in order to extract dominant principal components of biological bat flight kinematics.Thereafter, first and second principal components are chosen to shape the parametric kinematics and actuator trajectories of B2 through finite state nonlinear constrained optimization.The method yields a robot mechanism that despite having a few DoAs, it possesses several biologically meaningful morphing specializations.

This study evaluated the ability of eight existing ion and Hall thrusters to meet some of the key requirements of the OSIRIS-REx mission - to carry a dry mass of at least 750 kg to the asteroid 1999RQ36, land on it in 2019, stay on the asteroid for an extended period, and return with a sample of the asteroid to Earth. The thrusters were chosen based on demonstrated performance and lifetime characteristics at power levels higher than 5 kW, and were evaluated for this mission at their measured performance levels. The thrusters were evaluated for various values of the specific mass of the power plant and different values of stay time on the asteroid. The resulting values of total trip time and wet mass at LEO for the evaluated thrusters, for varying values of stay time on the asteroid, are presented and are compared with the existing plan of 7-year round-trip plan of the OSIRIS-REx mission with an Atlas-V class launch vehicle.