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An adaptive hierarchical control for aerial manipulators

Published online by Cambridge University Press:  30 July 2018

Francesco Pierri Open the ORCID record for Francesco Pierri [Opens in a new window] ,
Giuseppe Muscio  and
Fabrizio Caccavale
Francesco Pierri*
Affiliation:
Università degli Studi della Basilicata, Scuola di Ingegneria, via dell'Ateneo Lucano 10, Potenza 85100, Italy. E-mails: [email protected], [email protected]
Giuseppe Muscio
Affiliation:
Università degli Studi della Basilicata, Scuola di Ingegneria, via dell'Ateneo Lucano 10, Potenza 85100, Italy. E-mails: [email protected], [email protected]
Fabrizio Caccavale
Affiliation:
Università degli Studi della Basilicata, Scuola di Ingegneria, via dell'Ateneo Lucano 10, Potenza 85100, Italy. E-mails: [email protected], [email protected]
*
*Corresponding author. E-mail: [email protected]
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Summary

This paper addresses the trajectory tracking control problem for a quadrotor aerial vehicle, equipped with a robotic manipulator (aerial manipulator). The controller is organized in two layers: in the top layer, an inverse kinematics algorithm computes the motion references for the actuated variables; in the bottom layer, a motion control algorithm is in charge of tracking the motion references computed by the upper layer. To the purpose, a model-based control scheme is adopted, where modelling uncertainties are compensated through an adaptive term. The stability of the proposed scheme is proven by resorting to Lyapunov arguments. Finally, a simulation case study is proposed to prove the effectiveness of the approach.

Keywords

Aerial ManipulationAdaptive ControlModel-Based Control
Type
Articles
Information
Robotica , Volume 36 , Issue 10 , October 2018 , pp. 1527 - 1550
Copyright
Copyright © Cambridge University Press 2018 

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References

1. Doitsidis, L., Weiss, S., Renzaglia, A., Kosmatopoulos, E., Siegwart, R., Scaramuzza, D. and Achtelik, M., “Optimal surveillance coverage for teams of micro aerial vehicles in GPS-denied environments using onboard vision,” Auton. Robots 33 (1–2), 173–188 (2012).Google Scholar
2. Maza, I., Kondak, K., Bernard, M. and Ollero, A., “Multi-UAV cooperation and control for load transportation and deployment,” J. Intell. Robot. Syst. 57, 417–449 (2010).Google Scholar
3. Maza, I. and Ollero, A., “Autonomous transportation and deployment with aerial robots for search and rescue missions,” J. Field Robot. 28 (6), 914–931 (2011).Google Scholar
4. Merino, L., Caballero, F., Martinez-de-Dios, J., Maza, I. and Ollero, A., “An unmanned aircraft system for automatic forest fire monitoring and measurement,” J. Intell. Robot. Syst. 65 (1), 533–548 (2012).Google Scholar
5. How, J., Bethke, B., Frank, A., Dale, D. and Vian, J., “Real-time indoor autonomous vehicle test environment,” IEEE Control Syst. Mag. 28 (2), 51–64 (2008).Google Scholar
6. Civita, M. L., Papageorgiou, G., Messner, W. and Kanade, T., “Design and flight testing of an H ∞ controller for a robotic helicopter,” J. Guid., Control, Dyn. 29 (2), 485–494 (2006).Google Scholar
7. Kim, H. and Shim, D., “A flight control system for aerial robots: Algorithms and experiments,” Control Eng. Pract. 11 (2), 1389–1400 (2003).Google Scholar
8. Ahanda, J. J. B. M., Mbede, J. B., Melingui, A. and Essimbi, B., “Robust adaptive control for robot manipulators: Support vector regression-based command filtered adaptive backstepping approach,” Robotica 36 (4), 516–534 (2018).Google Scholar
9. Madani, T. and Benallegue, A., “Backstepping Sliding-Mode Control Applied to a Miniature Quadrotor Flying Robot,” Proceedings of the 32nd Annual Conference of the IEEE Industrial Electronics Society (2006) pp. 700–705.Google Scholar
10. Palunko, I. and Fierro, R., “Adaptive Control of a Quadrotor with Dynamic Changes in the Center of Gravity,” Proceedings of the 18th IFAC World Congress (2011) pp. 2626–2631.Google Scholar
11. Antonelli, G., Cataldi, E., Arrichiello, F., Giordano, P. R., Chiaverini, S. and Franchi, A., “Adaptive trajectory tracking for quadrotor mavs in presence of parameter uncertainties and external disturbances,” IEEE Trans. Control Syst. Technol. 26 (1), 248–254 (2018).Google Scholar
12. Kendoul, F., Fantoni, I. and Lozano, R., “Asymptotic Stability of Hierarchical Inner-Outer Loop-Based Flight Controllers,” Proceedings of the 17th IFAC World Congress (2008) pp. 1741–1746.Google Scholar
13. Pounds, P., Bersak, D. and Dollar, A., “Grasping from the air: Hovering capture and load stability,” Proceedings of IEEE International Conference on Robotics and Automation (2011) pp. 2491–2498.Google Scholar
14. Mellinger, D., Lindsey, Q., Shomin, M. and Kumar, V., “Design, Modelling, Estimation and Control for Aerial Grasping and Manipulation,” Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems (2011) pp. 2668–2673.Google Scholar
15. Ruggiero, F., Lippiello, V. and Ollero, A., “Aerial manipulation: A literature review,” IEEE Robot. Autom. Lett. 3 (3), 1957–1964 (2018).Google Scholar
16. Kondak, K., Krieger, K., Schaeffer, A. Albu and Ollero, A., “Closed-loop behavior of an autonomous helicopter equipped with a robotic arm for aerial manipulation tasks,” Int. J. Adv. Robot. Syst. 10, 1–9 (2013).Google Scholar
17. Huber, F., Kondak, K., Krieger, K., Sommer, D., Schwarzbach, M., Laiacker, M., Kossyk, I., Parusel, S., Haddadin, S. and Albu-Schaffer, A., “First Analysis and Experiments in Aerial Manipulation Using Fully Actuated Redundant Robot Arm,” Proceedings of the 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems (2013) pp. 3452–3457.Google Scholar
18. Kondak, K., Huber, F., Schwarzbach, M., Laiacker, M., Sommer, D., Bejar, M. and Ollero, A., “Aerial Manipulation Robot Composed of an Autonomous Helicopter and a 7 Degrees of Freedom Industrial Manipulator,” Proceedings of the IEEE International Conference on Robotics and Automation (2014) pp. 2107–2112.Google Scholar
19. Antonelli, G. and Cataldi, E., “Adaptive Control of Arm-Equipped Quadrotors. Theory and Simulations,” Proceedings of 22th Mediterranean Conference on Control and Automation (2014) pp. 1446–1451.Google Scholar
20. Fumagalli, M., Naldi, R., Macchelli, A., Forte, F., Keemink, A., Stramigioli, S., Carloni, R. and Marconi, L., “Developing an aerial manipulator prototype: Physical interaction with the environment,” IEEE Robot. Autom. Mag. 21 (3), 41–50 (2014).Google Scholar
21. Kim, S., Choi, S. and Kim, H., “Aerial Manipulation Using a Quadrotor with a Two dof Robotic Arm,” Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (2013) pp. 4990–4995.Google Scholar
22. Orsag, M., Korpela, C. and Oh, P., “Modeling and control of MM-UAV: Mobile manipulating unmanned aerial vehicle,” J. Intell. Robot. Syst. 69, 227–240 (2013).Google Scholar
23. Lippiello, V. and Ruggiero, F., “Cartesian Impedance Control of UAV with a Robotic Arm,” Proceedings of 10th International IFAC Symposium on Robot Control (2012) pp. 704–709.Google Scholar
24. Ryll, M., Muscio, G., Pierri, F., Cataldi, E., Antonelli, G., Caccavale, F. and Franchi, A., “6d Physical Interaction with a Fully Actuated Aerial Robot,” Proceedings of the IEEE International Conference on Robotics and Automation, IEEE (2017) pp. 5190–5195.Google Scholar
25. Arleo, G., Caccavale, F., Muscio, G. and Pierri, F., “Control of Quadrotor Aerial Vehicles Equipped with a Robotic Arm,” Proceedings of 21th Mediterranean Conference on Control and Automation (2013) pp. 1174–1180.Google Scholar
26. Kannan, S., Bezzaoucha, S., Guzman, S. Q., Dentler, J., Olivares-Mendez, M. A. and Voos, H., “Hierarchical Control of Aerial Manipulation Vehicle,” AIP Conference Proceedings, vol. 1798, AIP Publishing (2017) pp. 1–7.Google Scholar
27. Caccavale, F., Giglio, G., Muscio, G. and Pierri, F., “Adaptive Control for UAVs Equipped with a Robotic Arm,” Proceedings of the 19th World Congress The International Federation of Automatic Control (2014) pp. 11,049–11,054.Google Scholar
28. Baizid, K., Giglio, G., Pierri, F., Trujillo, M. A., Antonelli, G., Caccavale, F., Viguria, A., Chiaverini, S. and Ollero, A., “Behavioral control of unmanned aerial vehicle manipulator systems,” Auton. Robots 41 (5), 1203–1220 (2017).Google Scholar
29. Ren, J., Liu, D. X., Li, K., Liu, J., Feng, Y. and Lin, X., “Cascade PID Controller for Quadrotor,” Proceedings of the IEEE International Conference on Information and Automation (2016) pp. 120–124.Google Scholar
30. Siciliano, B., Sciavicco, L., Villani, L. and Oriolo, G., Robotics – Modelling, Planning and Control (Springer, London, UK, 2009).Google Scholar
31. Nonami, K., Kendoul, F., Suzuki, S. and Wang, W., Atonomous Flying Robots, Unmanned Aerial Vehicles and Micro Aerial Vehicles (Springer, London, UK, 2010).Google Scholar
32. Caccavale, F., Chiaverini, S. and Siciliano, B. “Second-order kinematic control of robot manipulators with jacobian damped least-squares inverse: Theory and experiments,” IEEE/ASME Trans. Mechatron. 2, 188–194 (1997).Google Scholar
33. Chiaverini, S. and Siciliano, B., “The unit quaternion: A useful tool for inverse kinematics of robot manipulators,” Syst. Anal. Model. Simul. 35, 45–60 (1999).Google Scholar
34. Muscio, G., Pierri, F., Trujillo, M., Cataldi, E., Antonelli, G., Caccavale, F., Viguria, A., Chiaverini, S. and Ollero, A. “Coordinated control of aerial robotic manipulators: Theory and experiments,” IEEE Trans. Control Syst. Technol. 26 (4), 1406–1413 (2018).Google Scholar
35. Hsu, P., Hauser, J. and Sastry, S., “Dynamic Control of Redundant Manipulators,” Proceedings of IEEE International Conference on Robotics and Automation, vol. 1, pp. 183–187 (1988).Google Scholar
36. Reger, J., Ramírez, H. S. and Fliess, M., “On Non-Asymptotic Observation of Nonlinear Systems,” Proceedings of the 44th IEEE Conference on Decision and Control, IEEE (2005) pp. 4219–4224.Google Scholar
37. Caccavale, F., Marino, A., Muscio, G. and Pierri, F., “Discrete-time framework for fault diagnosis in robotic manipulators,” IEEE Trans. Control Syst. Technol. 21 (5), 1858–1873.Google Scholar
38. Park, J. and Sandberg, I., “Universal approximation using radial-basis-function networks,” Neural Comput. 3, 246–257 (1991).Google Scholar
39. Khalil, H., Nonlinear Systems (2nd ed.) (Prentice Hall, Upper Saddle River, NJ, 1996).Google Scholar
40. Aström, K. and Wittenmark, B., Adaptive Control, 2nd ed. (Addison-Wesley, Reading, Massachusetts, 1995).Google Scholar
41. Ioannou, P. and Sun, J., Robust Adpative Control (Prentice Hall, Upper Saddle River, NJ, 1996).Google Scholar
42. Wang, C. and Hill, D. J., “Learning from neural control,” IEEE Trans. Neural Netw. 17 (1), 130–146 (2006).Google Scholar
43. Tayebi, A. and McGilvray, S., “Attitude stabilization of a vtol quadrotor aircraft,” IEEE Tr ans. Control Syst. Technol. 14 (3), 562–571 (2006).Google Scholar
44. Cano, R., Pérez, C., Pruaño, F., Ollero, A. and Heredia, G., “Mechanical Design of a 6-DOF Aerial Manipulator for Assembling Bar Structures Using UAVs,” Proceedings of the 2nd RED-UAS 2013 Workshop on Research, Education and Development of Unmanned Aerial Systems (2013).Google Scholar
45. ARCAS – Aerial Robotics Cooperative Assembly System. URL http://www.arcas-project.euGoogle Scholar
46. Castaldi, P., Mimmo, N., Naldi, R. and Marconi, L., “Robust Trajectory Tracking for Underactuated Vtol Aerial Vehicles: Extended for Adaptive Disturbance Compensation,” Proceedings of 19th IFAC World Congress, vol. 19 (2014) pp. 3184–3189.Google Scholar
47. Sontag, E., “A remark on the converging-input converging-state property,” IEEE Trans. Autom. Control 48 (2), 313–314 (2003).Google Scholar