Bioinspiration, Biomimicry, and Soft Robotics of Drones

A special issue of Drones (ISSN 2504-446X).

Deadline for manuscript submissions: closed (1 March 2023) | Viewed by 3105

Special Issue Editors

Institute of Unmanned System, Beihang University, Beijing 100191, China
Interests: unmanned system; bio-inspired MAV; flight control; motion/path planning
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Co-Guest Editor
Department of Mechanical and Aerospace Engineering, New Mexico State University, Las Cruces, NM 88003, USA
Interests: energy harvesting; nonlinear dynamics; vibration and control; smart materials; aeroelasticity; fluid-structure interactions; micro-/nanoelectromechanical systems (MEMS/NEMS); flight dynamics
Special Issues, Collections and Topics in MDPI journals

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Co-Guest Editor
Amazon, Seattle, WA 98109, USA
Interests: robotics

Special Issue Information

Dear Colleagues, 

Bionics has always been a vital way for human beings to make progress. By learning the advantages of different creatures, sensing and flight control strategies of current aerial vehicles have great potential to improve. For example, flies and dragonflies have large viewing angles and excellent dynamic visions thanks to their compound eyes; fish and reptiles have a 360-degree viewing angle due to their unique eye structure; birds can perceive subtle changes in the wind through the conduction of their feathers; insects rely on their flapping wings to generate sufficient lift and control torque under low Reynolds numbers. Such advantages motivate researchers and engineers to study new perception and propulsion principles. In fact, in recent years, bio-inspired sensing and control methods of drones have continued to attract the attention of scholars. By imitating the perception and propulsion mode of these creatures, several state-of-the-art drones have already implemented and demonstrated some bio-inspired sensing and flight control methods, leading the way in a young research field and showing significant research value and application prospects. With the development of manufacturing and integration technology, these bioinspired perception and control capabilities are more and more likely to be widely used in drones.

We seek research papers with contributions focusing on bioinspired sensing and control studies, including valuable principle research and the results of experiments on drones. Review papers that provide a comprehensive view of the fields of this research topic are welcome as well.

Dr. Zhan Tu
Dr. Abdessattar Abdelkefi
Dr. Fan Fei
Guest Editors

Manuscript Submission Information

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Keywords

  • bio-inspired sensing principle
  • bio-inspired sensors on drones
  • bio-inspired sensing method on drones
  • bio-inspired control principles
  • bio-inspired control mechanism on drones
  • bio-inspired control method on drones
  • bio-inspired motion planning on drones

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Published Papers (1 paper)

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Research

22 pages, 2982 KiB  
Article
Practically Robust Fixed-Time Convergent Sliding Mode Control for Underactuated Aerial Flexible JointRobots Manipulators
by Kamal Rsetam, Zhenwei Cao, Lulu Wang, Mohammad Al-Rawi and Zhihong Man
Drones 2022, 6(12), 428; https://doi.org/10.3390/drones6120428 - 19 Dec 2022
Cited by 14 | Viewed by 2233
Abstract
The control of an aerial flexible joint robot (FJR) manipulator system with underactuation is a difficult task due to unavoidable factors, including, coupling, underactuation, nonlinearities, unmodeled uncertainties, and unpredictable external disturbances. To mitigate those issues, a new robust fixed-time sliding mode control (FxTSMC) [...] Read more.
The control of an aerial flexible joint robot (FJR) manipulator system with underactuation is a difficult task due to unavoidable factors, including, coupling, underactuation, nonlinearities, unmodeled uncertainties, and unpredictable external disturbances. To mitigate those issues, a new robust fixed-time sliding mode control (FxTSMC) is proposed by using a fixed-time sliding mode observer (FxTSMO) for the trajectory tracking problem of the FJR attached to the drones system. First, the underactuated FJR is comprehensively modeled and converted to a canonical model by employing two state transformations for ease of the control design. Then, based on the availability of the measured states, a cascaded FxTSMO (CFxTSMO) is constructed to estimate the unmeasurable variables and lumped disturbances simultaneously in fixed-time, and to effectively reduce the estimation noise. Finally, the FxTSMC scheme for a high-order underactuated FJR system is designed to guarantee that the system tracking error approaches to zero within a fixed-time that is independent of the initial conditions. The fixed-time stability of the closed-loop system of the FJR dynamics is mathematically proven by the Lyapunov theorem. Simulation investigations and hardware tests are performed to demonstrate the efficiency of the proposed controller scheme. Furthermore, the control technique developed in this research could be implemented to the various underactuated mechanical systems (UMSs), like drones, in a promising way. Full article
(This article belongs to the Special Issue Bioinspiration, Biomimicry, and Soft Robotics of Drones)
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