For aerial manipulators, a steady flight must be guaranteed to perform safe interaction with the surrounding environment. This paper focuses on the development of a position control algorithm for an aerial manipulator system (AMS). The position control algorithm is based on the Immersion and Invariance (I&I) theory. The proposed controller maintains the position of the aerial manipulator at the desired point under external and internal disturbances. The control architecture uses a Visual-SLAM technique using on-board sensors for AMS positioning. A series of outdoor experimental tests are performed to demonstrate the effectiveness of the proposed control strategy.

This paper was recommended for publication in its revised form by coeditor-in-chief, Ben M. Chen.

Keywords:

References

1. T. Bartelds, A. Capra, S. Hamaza, S. Stramigioli and M. Fumagalli, Compliant aerial manipulators: Toward a new generation of aerial robotic workers, IEEE Robot. Autom. Lett. 1(1) (2016) 477–483. Crossref, Google Scholar
2. T. Wang, K. Umemoto, T. Endo and F. Matsuno, Dynamic hybrid position/force control for the quadrotor with a multi-degree-of-freedom manipulator, Artif. Life Robot. 24(3) (2019) 378–389. Crossref, Google Scholar
3. A. L. Luna, I. C. Vega and J. Martinez-Carranza, Towards micro aerial manipulation using a computational compensation strategy, in 10th Int. Micro Air Vehicle Competition and Conf. (IMAV 2018), Vol. 11 (2018). Google Scholar
4. F. Huber, K. Kondak, K. Krieger, D. Sommer, M. Schwarzbach, M. Laiacker, I. Kossyk, S. Parusel, S. Haddadin and A. Albu-Schiffer, First analysis and experiments in aerial manipulation using fully actuated redundant robot arm, in 2013 IEEE/RSJ Int. Conf. Intelligent Robots and Systems (2013), pp. 3452–3457. Crossref, Google Scholar
5. C. Korpela, P. Brahmbhatt, M. Orsag and P. Oh, Towards the realization of mobile manipulating unmanned aerial vehicles (MM-UAV): Peg-in-hole insertion tasks, in 2013 IEEE Int. Conf. Technologies for Practical Robot Applications (TePRA) (2013), pp. 1–6. Crossref, Google Scholar
6. H. Lee, S. Kim and H. J. Kim, Control of an aerial manipulator using on-line parameter estimator for an unknown payload, in 2015 IEEE Int. Conf. Automation Science and Engineering (CASE) (2015), pp. 316–321. Crossref, Google Scholar
7. S. Di Lucia, G. D. Tipaldi and W. Burgard, Attitude stabilization control of an aerial manipulator using a quaternion-based backstepping approach, in 2015 Eur. Conf. Mobile Robots (ECMR) (IEEE, 2015), pp. 1–6. https://doi.org/10.1109/ECMR.2015.7324191. Crossref, Google Scholar
8. A. Zulu and S. John, A review of control algorithms for autonomous quadrotors, CoRR (2016) abs/1602.02622. Google Scholar
9. A. Dollar and P. E. I. Pounds, Hovering stability of helicopters with elastics constraints, ASME Dynamic Systems and Control Conf. (2010). Google Scholar
10. M. Orsag, C. Korpela and P. Oh, Modeling and control of MM-UAV: Mobile manipulating unmanned aerial vehicle, J. Intell. Robot. Syst. 69(1) (2013) 227–240. Crossref, Google Scholar
11. A. Astolfi and R. Ortega, Immersion and invariance: A new tool for stabilization and adaptive control of nonlinear systems, IEEE Trans. Autom. Control 48(4) (2003) 590–606. Crossref, Google Scholar
12. J. Hu and H. Zhang, Immersion and invariance based command-filtered adaptive backstepping control of VTOL vehicles, Automatica 49(7) (2013) 2160–2167. Crossref, Google Scholar
13. L. Wang, F. Forni, R. Ortega and H. Su, Immersion and invariance stabilization of nonlinear systems: A horizontal contraction approach, in 2015 54th IEEE Conf. Decision and Control (CDC) (IEEE, 2015), pp. 3093–3097. https://doi.org/10.1109/cdc.2015.7402684. Crossref, Google Scholar
14. Y. Bouzid, H. Siguerdidjane and Y. Bestaoui, Real time autopilot based on immersion & invariance for autonomous aerial vehicle, IFAC-PapersOnLine 49(17) (2016) 176–181, 20th IFAC Symp. Automatic Control in Aerospace (ACA) 2016. Google Scholar
15. G. Tagne, R. Talj and A. Charara, Immersion and invariance control for reference trajectory tracking of autonomous vehicles, in 16th Int. IEEE Conf. Intelligent Transportation Systems (ITSC 2013) (IEEE, 2013), pp. 2322–2328. https://doi.org/10.1109/ITSC.2013.6728574. Crossref, Google Scholar
16. X. Li, H. Zhang, W. Fan, J. Zhao and C. Wang, Multivariable finite-time composite control strategy based on immersion and invariance for quadrotor under mismatched disturbances, Aerosp. Sci. Technol. 99(2) (2020) 105763. Crossref, Google Scholar
17. L. O. Rojas-Perez and J. Martinez-Carranza, Metric monocular slam and colour segmentation for multiple obstacle avoidance in autonomous flight, in 2017 Workshop on Research, Education and Development of Unmanned Aerial Systems (RED-UAS) (IEEE, 2017), pp. 234–239. https://doi.org/10.1109/RED-UAS.2017.8101672. Crossref, Google Scholar
18. J. J. Corona-Sánchez and H. Rodríguez-Cortés, Trajectory tracking control for a rotary wing vehicle powered by four rotors, J. Intell. Robot. Syst. 70(1) (2013) 39–50. Crossref, Google Scholar
19. M. Fecko, Differential Geometry and Lie Groups for Physicists (Cambridge University Press, 2006). Crossref, Google Scholar
20. B. L. Stevens, F. L. Lewis and E. N. Johnson, Aircraft Control and Simulation: Dynamics, Controls Design, and Autonomous Systems (John Wiley & Sons, 2015). Crossref, Google Scholar
21. E. A. Morelli and V. Klein, Aircraft System Identification: Theory and Practice, Vol. 2 (Sunflyte Enterprises, Williamsburg, VA, 2016). Google Scholar
22. Y. Huang and W. Xue, Active disturbance rejection control: Methodology and theoretical analysis, ISA Trans. 53(4) (2014) 963–976, Disturbance Estimation and Mitigation. Crossref, Google Scholar
23. R. Seeber, M. Horn and L. Fridman, A novel method to estimate the reaching time of the super-twisting algorithm, IEEE Trans. Autom. Control 63(12) (2018) 4301–4308. Crossref, Google Scholar
24. A. L. Luna, I. C. Vega and J. Martinez-Carranza, Gain-scheduling and pid control for an autonomous aerial vehicle with a robotic arm, in 2018 IEEE 2nd Colombian Conf. Robotics and Automation (CCRA) (IEEE, 2018), pp. 1–6. https://doi.org/10.1109/CCRA.2018.8588145. Crossref, Google Scholar
25. A. L. Luna, J. Martinez-Carranza and I. C. Vega, Towards aerial interaction of MAVs in GPS-denied environments, in 2019 Workshop on Research, Education and Development of Unmanned Aerial Systems (RED UAS) (IEEE, 2019), pp. 113–121. https://doi.org/10.1109/REDUAS47371.2019.8999686. Crossref, Google Scholar
26. H. Moon, J. Martinez-Carranza, T. Cieslewski, M. Faessler, D. Falanga, A. Simovic, D. Scaramuzza, S. Li, M. Ozo, C. De Wagter, G. de Croon, S. Hwang, S. Jung, H. Shim, H. Kim, M. Park, T.-C. Au and S. J. Kim, Challenges and implemented technologies used in autonomous drone racing, Intell. Serv. Robot. 12(2) (2019) 137–148. Crossref, Google Scholar