Mobile Autonomous Recovery Landing Principle and Control Method for Unmanned Aerial Vehicle

doi:10.3901/JME.2024.03.034

Abstract

Abstract: Aiming at the problems of relatively fixed landing point, passive recovery, poor flexibility and environmental adaptability of unmanned aerial vehicle (UAV) recovery landing, a fully autonomous ground mobile recovery principle of UAV is proposed, including UAV localization, landing point tracking, and the active flexible undertaking to realize autonomous UAV dynamic mobile recovery landing in the complex environment in the field. Firstly, in order to guarantee the accuracy of acquiring the dynamic position of UAV, a target localization method with multi-sensor information fusion localization and servo turntable tracking is proposed. Secondly, to achieve fast and high-precision tracking of UAV, a two-stage tracking control strategy based on unmanned ground vehicle (UGV) and Stewart platform is proposed. Finally, to solve the problems of large impact and center of gravity instability in the landing process of UAV, a stability control algorithm based on model prediction and a compliance control algorithm based on adaptive variable impedance are designed to achieve active compliance while adjusting the position and attitude of the receiving surface in real time. A principle prototype consisting of a localization device, UGV, and Stewart platform was built to verify the feasibility of the principle and the effectiveness of the control algorithm. The scheme and technology have been successfully applied to the autonomous recovery of a fixed wing UAV.

Key words: unmanned aerial vehicle, mobile autonomous recovery, target positioning, falling point tracking, flexible undertaking

CLC Number:

TP24

WANG Shoukun, XU Yongkang, CHEN Zhihua, SI Jinge, LI Bin, WANG Junzheng. Mobile Autonomous Recovery Landing Principle and Control Method for Unmanned Aerial Vehicle[J]. Journal of Mechanical Engineering, 2024, 60(3): 34-46.

References

[1] 白光晗,张驰,兑红炎,等.无人机集群任务可靠性建模及重要度分析[J].机械工程学报, 2022, 58(10):361-373. BAI Guanghan, ZHANG Chi, DUI Hongyan, et al. Reliability modeling and importance analysis of UAV swarm[J]. Journal of Mechanical Engineering, 2022, 58(10):361-373.
[2] 吴西涛,魏超,翟建坤,等.考虑横摆稳定性的无人车轨迹跟踪控制优化研究[J].机械工程学报, 2022, 58(6):130-142. WU Xitao, WEI Chao, ZHAI Jiankun, et al. Study on the optimization of autonomous vehicle on path-following considering yaw stability[J]. Journal of Mechanical Engineering, 2022, 58(6):130-142.
[3] YANG S, XI L, HAO J, et al. Aerodynamic-parameter identification and attitude control of quad-rotor model with CIFER and adaptive LADRC[J]. Chinese Journal of Mechanical Engineering, 2021, 34(2):1.
[4] CHU W, WUNIRI Q, DU X, et al. Cloud control system architectures, technologies and applications on intelligent and connected vehicles:a review[J]. Chinese Journal of Mechanical Engineering, 2021, 34(5):139.
[5] 鲁亚飞,陈清阳,王鹏,等.中小型固定翼无人机精确回收技术发展与关键技术分析[J].飞航导弹, 2020(4):59-65. LU Yafei, CHEN Qingyang, WANG Peng, et al. Development and key technology analysis of precise recovery technology for small and medium-sized fixed wing UAV[J]. Aerodynamic Missile Journal, 2020(4):59-65.
[6] MAZA I, CABALLERO F, CAPITAB J, et al. Experimental results in multi-UAV coordination for disaster management and civil security applications[J]. Journal of Intelligent & Robotic Systems, 2011, 61:563-585.
[7] WYLLIE T. Parachute recovery for UAV systems[J]. Aircraft Engineering and Aerospace Technology, 2001, 73(6):542-551.
[8] KIM H J, KIM M, LIM H, et al. Fully autonomous vision-based net-recovery landing system for a fixed-wing UAV[J]. IEEE/ASME Transactions on Mechatronics, 2013, 18(4):1320-1333.
[9] BORNEBUSH M F, JOHANSEN T A. Autonomous recovery of a fixed-wing UAV using a line suspended between two multirotor UAVs[J]. IEEE Transactions on Aerospace and Electronic Systems, 2020, 57(1):90-104.
[10] PATRUNO C, NITTI M, PETITTI A, et al. A vision-based approach for unmanned aerial vehicle landing[J]. Journal of Intelligent & Robotic Systems, 2019, 95(2):645-664.
[11] REDDING J D, MCLAIN T W, BEARD R W, et al. Vision-based target localization from a fixed-wing miniature air vehicle[C]//IEEE American Control Conference, June 14-16, 2006, Minneapolis, MN, USA. IEEE, 2006:2862-2867.
[12] SHARP C S, SHAKERNIA O, SASTRY S S. A vision system for landing an unmanned aerial vehicle[C]//Proceedings 2001 ICRA. IEEE International Conference on Robotics and Automation, May 21-26, 2001. Seoul, Korea. IEEE, 2001:1720-1727.
[13] KONG W, ZHOU D, ZHANG Y, et al. A ground-based optical system for autonomous landing of a fixed wing UAV[C]//2014 IEEE/RSJ International Conference on Intelligent Robots and Systems. September 14-18, 2014, Chicago, IL, USA. IEEE, 2014:4797-4804.
[14] ACHTELIK M, ZHANG T, KUHNLENZ K, et al. Visual tracking and control of a quadcopter using a stereo camera system and inertial sensors[C]//2009 International Conference on Mechatronics and Automation, August 9-12, 2009. Changchun, China. IEEE, 2009:2863-2869.
[15] KALINOV I, SAFRONOV E, AGISHEV R, et al. High-precision UAV localization system for landing on a mobile collaborative robot based on an IR marker pattern recognition[C]//2019 IEEE 89th Vehicular Technology Conference (VTC2019-Spring), 28 April-01 May, 2019. Kuala Lumpur, Malaysia. IEEE, 2019:1-6.
[16] YU Xianjia, LI Qingqing, QUERALTA J P, et al. Cooperative uwb-based localization for outdoors positioning and navigation of UAVs aided by ground robots[C]//2021 IEEE International Conference on Autonomous Systems (ICAS), August 11-13, 2021. Montreal, QC, Canada. IEEE, 2021:1-5.
[17] 伍明,孙继银.基于扩展式卡尔曼滤波的移动机器人未知环境下动态目标跟踪[J].机器人, 2010, 32(3):334-343. WU Ming, SUN Jiyin. Extended Kalman filter based moving object tracking by mobile robot in unknown environment[J]. Robot, 2010, 32(3):334-343.
[18] JAYASREE K R, JAYASREE P R, VIVEK A. Dynamic target tracking using a four wheeled mobile robot with optimal path planning technique[C]//2017 International Conference on Circuit, Power and Computing Technologies (ICCPCT),April 20-21,2017. Kollam,India. IEEE, 2017:1-6.
[19] WEI Y, ZHU D, CHU Z. Underwater dynamic target tracking of autonomous underwater vehicle based on MPC algorithm[C]//2018 IEEE 8th International Conference on Underwater System Technology:Theory and Applications (USYS), December 1-3, 2018. Wuhan, China. IEEE, 2018:1-5.
[20] QUINTERO S A P, COPP D A, HESPANHA J P. Robust coordination of small UAVs for vision-based target tracking using output-feedback MPC with MHE[J]. Cooperative Control of Multi-Agent Systems:Theory and Applications, 2017(1):51-83.
[21] ASHE A, KRISHNA K M. Dynamic target tracking & collision avoidance behaviour of person following robot using model predictive control[C]//2020 24th International Conference on System Theory, Control and Computing (ICSTCC), October 8-10, 2020. Sinaia, Romania. IEEE, 2020:660-666.
[22] FASSE E D, GOSSELIN C M. Spatio-geometric impedance control of gough-stewart platforms[J]. IEEE Transactions on Robotics and Automation, 1999, 15(2):281-288.
[23] DAVLIAKOS I, PAPADOPOULOS E. A model-based impedance control of a 6-DOF electrohydraulic Stewart platform[C]//2007 European Control Conference (ECC), July 2-5, 2007. Kos, Greece. IEEE, 2007:3507-3514.
[24] ZHANG Hao, WANG Shoukun, YAN Z, et al. Stewart-inspired posture control for a UAV undertaking platform based on dynamic model predictive control[C]//2021 China Automation Congress (CAC), October 22-24, 2021. Beijing, China. IEEE, 2021:3601-3606.
[25] GODARDC, MAC A O, FIRMAN M, et al. Digging into self-supervised monocular depth estimation[C]//Proceedings of the IEEE/CVF International Conference on Computer Vision, 2019:3828-3838.