Design and dynamic analysis of a Transformable Hovering Rotorcraft (THOR)

Low, Jun En; Win, Luke Thura Soe; Shaiful, Danial Sufiyan bin; Tan, Chee How; Soh, Gim Song; Foong, Shaohui

doi:10.1109/icra.2017.7989755

Cited by 40 publications

(15 citation statements)

References 3 publications

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“…Due to the sophisticated aerodynamics and flight trajectories, the authors carried out over 100 iterations to reach the two final designs that have the lift-to-weight ratios of 1.67 and 1.36. Another related robot is presented as a 532-gram hybrid robot with a 105-cm wingspan [9].…”

Section: Introductionmentioning

confidence: 99%

Design and Take-Off Flight of a Samara-Inspired Revolving-Wing Robot

Bai

Chirarattananon

2019

2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

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Motivated by a winged seed, which takes advantage of a wing with high angles of attack and its associated leading-edge vortex to boost lift, we propose a powered 13.8gram aerial robot with the maximum take-off weight of 310 mN (31.6 gram) or thrust-to-weight ratio of 2.3. The robot, consisting of two airfoils and two horizontally directed motordriven propellers, revolves around its vertical axis to hover. To amplify the thrust production while retaining a minimal weight, we develop an optimization framework for the robot and airfoil geometries. The analysis integrates quasi-steady aerodynamic models for the airfoils and the propellers with the motor model. We fabricated the robots according to the optimized design. The prototypes are experimentally tested. The revolving-wing robot produces approximately 50% higher lift compared to conventional multirotor designs. Finally, an uncontrolled hovering flight is presented.

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Section: Introductionmentioning

confidence: 99%

Design and Take-Off Flight of a Samara-Inspired Revolving-Wing Robot

Bai

Chirarattananon

2019

2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

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“…The THOR evolved from the conventional nature-inspired asymmetrical single-wing monocopter platform [1] [2] [3] [4] to a symmetrical dual-wing design for excellent hovering characteristics with increased payload. Also, its integrated transformation mechanism rotates the wings from hovering to fixed-wing configuration to achieve aerodynamically efficient long-range flight [5]. Whereas recent work primarily focuses on the control [6] [7], state sensing [8] and estimation [9], and the mechanical design [5] of the THOR, this work advances the applications of the THOR as a flying lidar sensor for SLAM.…”

Section: Introductionmentioning

confidence: 99%

Flydar: A Passive Scanning Flying Lidar Sensing System for SLAM Using a Single Laser

et al. 2022

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This paper presents the Flying Lidar (Flydar) aerial robot for simultaneous localization and mapping (SLAM). The Flydar integrates a single laser and capitalizes on the rotating dynamics of a nature-inspired aerial robot for omnidirectional scanning. This paper presents a 2.5D SLAM approach using the Flydar and does not assume that the Flydar's hovering plane, and thus the laser scan, is parallel to the ground plane, which is a key assumption in our previous work. A quaternion-based filter performs active correction of the Flydar's laser scan due to its transient attitude. A dual-accelerometer approach was incorporated to estimate the Flydar's scan rate during high angular rates flight beyond the gyroscope dynamic range. The proposed attitude filter output was experimentally evaluated statically on a bench-top setup and dynamically in flight, with an rms inclination estimate error of up to 1.1 o and 0.38 o respectively. The attitudecorrected lidar scan was used to estimate the robot pose for 2.5D SLAM. The 2.5D SLAM was experimentally validated on the Flydar and demonstrated to be superior to pure 2D SLAM in loop closure, position estimate drift, and rms error. Significantly, the 2.5D SLAM using the Flydar reports a low rms Euclidean error of up to 0.083 m, which is a 32.0% error reduction compared with our previous work, which uses 2D SLAM.

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“…Recently, UAVs have received much attention and importance due to their autonomy and flexibility and have been extensively utilized in various fields, such as wireless communication [2]- [4], military [5] [6], surveillance and monitoring [7] [8], smart agriculture [9], delivery of medical supplies [10], and rescue operations [11] [12]. In the most recent research work, UAVs have been used to enhance the capabilities of the MEC systems.…”

Section: Introductionmentioning

confidence: 99%

A Novel Genetic Trajectory Planning Algorithm With Variable Population Size for Multi-UAV-Assisted Mobile Edge Computing System

Asim

Khan²,

Belhaouari

et al. 2021

IEEE Access

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This paper presents a multi-unmanned aerial vehicle (UAV)-assisted mobile edge computing (MEC) system, where multiple UAVs (variable number of UAVs) are deployed to serve Internet of Things devices (IoTDs). We aim to minimize the sum of hovering and flying energies of UAVs by optimizing the trajectories of UAVs. The problem is very complicated as we have to consider the deployment of stop points (SPs), the association between UAVs and SPs, and the order of SPs for UAVs. To solve the problem, this paper proposed a novel genetic trajectory planning algorithm with variable population size (GTPA-VP), which consists of two phases. In the first phase, operators of GA with a variable population size are used to update the deployment of SPs. Accordingly, multi-chrome GA is adopted to find the association between UAVs and SPs, an optimal number of UAVs, and the optimal order of SPs for UAVs. The effectiveness of the proposed GTPA-VP is demonstrated through several experiments on a set of ten instances with up to 200 IoTDs. It is evident from the experimental results that the proposed GTPA-VP outperforms the benchmark algorithms in terms of the energy consumption of the system. INDEX TERMS Mobile edge computing, unmanned aerial vehicle, evolutionary algorithm, multi-chrome genetic algorithm.

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Design and dynamic analysis of a Transformable Hovering Rotorcraft (THOR)

Cited by 40 publications

References 3 publications

Design and Take-Off Flight of a Samara-Inspired Revolving-Wing Robot

Design and Take-Off Flight of a Samara-Inspired Revolving-Wing Robot

Flydar: A Passive Scanning Flying Lidar Sensing System for SLAM Using a Single Laser

A Novel Genetic Trajectory Planning Algorithm With Variable Population Size for Multi-UAV-Assisted Mobile Edge Computing System

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