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1. Modeling and Control of Swing Oscillation of Underactuated Indoor Miniature Autonomous Blimps

   https://doi.org/10.1142/S2301385021500060  

   Tao, Qiuyang; Tan, Tun Jian; Cha, Jaeseok; Yuan, Ye; Zhang, Fumin (January 2021, Unmanned Systems)

   null (Ed.)

   Swing oscillation is widely observed among indoor miniature autonomous blimps (MABs) due to their underactuated design and unique aerodynamic shape. This paper presents the modeling, identification and control system design that reduce the swing oscillation of an MAB during hovering flight. We establish a dynamic model to describe the swing motion of the MAB. The model parameters are identified from both physical measurements, computer modeling and experimental data captured during flight. A control system is designed to stabilize the swing motion with features including low latency and center-of-mass (CM) position estimation. The modeling and control methods are verified with the Georgia-Tech Miniature Autonomous Blimp (GT-MAB) during hovering flight. The experimental results show that the proposed methods can effectively reduce the swing oscillation of GT-MAB. 

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2. A Deep Learning Approach to Localization for Navigation on a Miniature Autonomous Blimp

   https://doi.org/10.1109/ICCA51439.2020.9264514  

   Seguin, Landan; Zheng, Justin; Li, Alberto; Tao, Qiuyang; Zhang, Fumin (October 2020, IEEE International Conference on Control and Automation (ICCA))

   null (Ed.)

   The Georgia Tech Miniature Autonomous Blimp (GT-MAB) needs localization algorithms to navigate to way-points in an indoor environment without leveraging an external motion capture system. Indoor aerial robots often require a motion capture system for localization or employ simultaneous localization and mapping (SLAM) algorithms for navigation. The proposed strategy for GT-MAB localization can be accomplished using lightweight sensors on a weight-constrained platform like the GT-MAB. We train an end-to-end convolutional neural network (CNN) that predicts the horizontal position and heading of the GT-MAB using video collected by an onboard monocular RGB camera. On the other hand, the height of the GT-MAB is estimated from measurements through a time-of-flight (ToF) single-beam laser sensor. The monocular camera and the single-beam laser sensor are sufficient for the localization algorithm to localize the GT-MAB in real time, achieving the averaged 3D positioning errors to be less than 20 cm, and the averaged heading errors to be less than 3 degrees. With the accuracy of our proposed localization method, we are able to use simple proportional-integral-derivative controllers to control the GT-MAB for waypoint navigation. Experimental results on the waypoint following are provided, which demonstrates the use of a CNN as the primary localization method for estimating the pose of an indoor robot that successfully enables navigation to specified waypoints. 

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3. Elephant Trunk Inspired Multimodal Deformations and Movements of Soft Robotic Arms

   https://doi.org/10.1002/adfm.202400396  

   Leanza, Sophie; Lu‐Yang, Juliana; Kaczmarski, Bartosz; Wu, Shuai; Kuhl, Ellen; Zhao, Ruike_Renee (February 2024, Advanced Functional Materials)

   Abstract Elephant trunks are capable of complex, multimodal deformations, allowing them to perform task‐oriented high‐degree‐of‐freedom (DOF) movements pertinent to the field of soft actuators. Despite recent advances, most soft actuators can only achieve one or two deformation modes, limiting their motion range and applications. Inspired by the elephant trunk musculature, a liquid crystal elastomer (LCE)‐based multi‐fiber design strategy is proposed for soft robotic arms in which a discrete number of artificial muscle fibers can be selectively actuated, achieving multimodal deformations and transitions between modes for continuous movements. Through experiments, finite element analysis (FEA), and a theoretical model, the influence of LCE fiber design on the achievable deformations, movements, and reachability of trunk‐inspired robotic arms is studied. Fiber geometry is parametrically investigated for 2‐fiber robotic arms and the tilting and bending of these arms is characterized. A 3‐fiber robotic arm is additionally studied with a simplified fiber arrangement analogous to that of an actual elephant trunk. The remarkably broad range of deformations and the reachability of the arm are discussed, alongside transitions between deformation modes for functional movements. It is anticipated that this design and actuation strategy will serve as a robust method to realize high‐DOF soft actuators for various engineering applications. 

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4. Wind tunnel experiments and model predictions of the performance of a floating offshore wind turbine undergoing pitch motion

   https://doi.org/10.1063/5.0301237  

   Panthi, Keshav; Iungo, Giacomo Valerio (December 2025, Journal of Renewable and Sustainable Energy)

   Floating offshore wind turbines (FOWTs) experience multiple degree-of-freedom (DOF) motion as a result of the non-linear interactions between the aerodynamic and hydrodynamic forces exerted on the turbine rotor and the floating platform, respectively, which create complex dynamics for FOWT operations and, in turn, variability in rotor angular speed and power capture. In this work, wind tunnel experiments are performed with a down-scaled FOWT model installed on top of a robotic emulator that reproduces 4-DOF motions. Rotor rotational speed, ω, and power capture are measured for pitch motions with different amplitudes and frequencies. These experimental data are first analyzed, then used for the validation of a non-linear dynamic analytical model that predicts the variation in ω and power capture by leveraging the aerodynamic quasi-steady assumption, namely, the FOWT power curve measured under static conditions and null pitch angle is used to predict operations under dynamic conditions. The results show that good accuracy is generally achieved with the analytical model. However, dynamic aerodynamic effects occur during pitch motion that can jeopardize the accuracy of the analytical model, especially with increasing ω, motion amplitude, and in correspondence with pitch angles where the inversion of the motion direction occurs. Furthermore, it is found that these dynamic aerodynamic effects can be accurately predicted through a random forest model by providing as input pitch angle, velocity, and acceleration of the incoming wind. Among the different FOWT motion parameters, the pitch angle is found to be the most influential factor for the magnitude of the dynamic aerodynamic effects. 

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5. Design of an Articulated Modular Caterpillar Using Spherical Linkages

   https://doi.org/10.1109/ICRA55743.2025.11127993  

   O'Connor, Sam; Plecnik, Mark (May 2025, IEEE Xplore)

   Articulation between body segments of small insects and animals is a three degree-of-freedom (DOF) motion. Implementing this kind of motion in a compact robot is usually not tractable due to limitations in small actuator technologies. In this work, we concede full 3-DOF control and instead select a one degree-of-freedom curve in SO(3) to articulate segments of a caterpillar robot. The curve is approximated with a spherical four-bar, which is synthesized through optimal rigid body guidance. We specify the desired SO(3) motion using discrete task positions, then solve for candidate mechanisms by computing all roots of the stationary conditions using numerical homotopy continuation. A caterpillar robot prototype demonstrates the utility of this approach. This synthesis procedure is also used to design prolegs for the caterpillar robot. Each segment contains two DC motors and a shape memory alloy, which is used for latching and unlatching between segments. The caterpillar robot is capable of walking, steering, object manipulation, body articulation, and climbing. 

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