REFERENCES
1. Hassanalian M, Abdelkefi A. Classifications, applications, and design challenges of drones: a review. Prog Aerosp Sci 2017;91:99-131.
2. Liu SK, Atanasov N, Mohta K, Kumar V. Search-based motion planning for quadrotors using linear quadratic minimum time control. In: IEEE/RSJ international conference on intelligent robots and systems (IROS); 2017. p. 2872-2879.
3. Zhou X, Wang ZP, Ye HK, Xu C, Gao F. Ego-planner: An ESDF-free gradient-based local planner for quadrotors. IEEE Robot and Autom Lett 2020;6:478-85.
4. Tothong T, Samawi J, Govalkar A, George K. Morphing quadcopters: a comparison between proposed and prominent foldable quadcopters. In: IEEE Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON); 2020. p. 589-96.
5. Bucki N, Mueller MW. Design and control of a passively morphing quadcopter. In: IEEE International Conference on Robotics and Automation (ICRA); 2019. p. 9116-22.
6. Zhao N, Luo YD, Deng HB, Shen YT. The deformable quad-rotor: design, kinematics and dynamics characterization, and flight performance validation. In: IEEE/RSJ international conference on intelligent robots and systems (IROS); 2017. p. 2391-6.
7. Falanga D, Kleber K, Mintchev S, Floreano D, Scaramuzza D. The foldable drone: a morphing quadrotor that can squeeze and fly. IEEE Robot Autom Lett 2019;4:209-216.
8. Fabris A, Kleber K, Falanga D, Scaramuzza D. Geometry-aware compensation scheme for morphing drones. In: IEEE International Conference on Robotics and Automation (ICRA) 2021. p. 592-8.
9. Kim C, Lee H, Jeong M, Hyun M. A morphing quadrotor that can optimize morphology for transportation. In: IEEE/RSJ international conference on intelligent robots and systems (IROS); 2021. p. 9683-9.
10. Sakaguchi A, Yamamoto K. A novel quadrotor with a 3-Axis deformable frame using tilting motions of parallel link modules without thrust loss. IEEE Robot Autom Lett 2022;7:9581-8.
11. Wu YZ, Yang F, Wang Z, Wang KW, Cao Y, et al. Ring-rotor: a novel retractable ring-shaped quadrotor with aerial grasping and transportation capability. IEEE Robot Autom Lett 2023;8:2126-33.
12. Zhang Z, Yang Z, Duan YX, Liao LW, Lu KW, et al. Active disturbance rejection control method for actively deformable quadrotor. Control Theory and Applications 2021;38:444-56.
13. Chen ZQ, Liu JJ, Sun MW. Overview of a novel control method: active disturbance rejection control technology and its practical applications. CAAI Trans Intell Syst 2018;13:865-877.
14. Han JQ. From PID to active disturbance rejection control. IEEE Trans Ind Electron 2009;56:900-6.
15. Lu YH, Han LY, Liu JH, Li SH. Model predictive tracking control for rigid manipulators with disturbance rejection. In: Chinese Control Conference (CCC); 2022. p. 9683-9.
16. Wang JX, Rong JY, Yang J. Adaptive fixed-time position precision control for magnetic levitation systems. IEEE Trans Automat Sci Eng 2023;20:458-69.
17. Ren C, Ma SG. Generalized proportional integral observer based control of an omnidirectional mobile robot. Mechatronics 2015;26:36-44.
18. Xia YQ, Lin M, Zhang JH, Fu MY, Li CM, et al. Trajectory planning and tracking for four‐wheel steering vehicle based on differential flatness and active disturbance rejection controller. Int J Adapt Control Signal Process 2021;35:2214-44.
19. Liu GD, Sun N, Yang T, Fang YC. Reinforcement learning-based prescribed performance motion control of pneumatic muscle actuated robotic arms with measurement noises. IEEE Trans Syst Man Cybern: Syst 2023;53:1801-12.