Hostname: page-component-cd9895bd7-7cvxr Total loading time: 0 Render date: 2024-12-25T17:36:49.372Z Has data issue: false hasContentIssue false
  • English
  • Français

A strategy for safe 3D navigation of non-holonomic robots among moving obstacles

Published online by Cambridge University Press:  10 November 2017

Chao Wang ,
Andrey V. Savkin  and
Matthew Garratt
Chao Wang*
Affiliation:
School of Electrical Engineering and Telecommunications, The University of New South Wales, Sydney 2052, Australia. E-mail: a.savkin@unsw.edu.au
Andrey V. Savkin
Affiliation:
School of Electrical Engineering and Telecommunications, The University of New South Wales, Sydney 2052, Australia. E-mail: a.savkin@unsw.edu.au
Matthew Garratt
Affiliation:
School of Engineering and Information Technology, The University of New South Wales, Canberra 2600, Australia. E-mail: m.garratt@adfa.edu.au
*
*Corresponding author. E-mail: z3184703@zmail.unsw.edu.au
Get access Rights & Permissions [Opens in a new window]

Summary

A non-holonomic robot with a bounded control input travels in a dynamic unknown 3D environment with moving obstacles. We propose a 3D navigation strategy to reach a given final destination point while avoiding collisions with obstacles. A formal analysis of the proposed 3D robot navigation algorithm is given. Computer simulation results and experiments with a real flying autonomous vehicle confirm the applicability and performance of the proposed guidance approach.

Keywords

Guidance3D navigationMoving obstaclesSense-and-avoidCollision avoidanceFlying robotsUnderwater robotsObstacle avoidanceNon-holonomic robotsNavigation in dynamic unknown environments
Type
Articles
Information
Robotica , Volume 36 , Issue 2 , February 2018 , pp. 275 - 297
Copyright
Copyright © Cambridge University Press 2017 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

1. James, A., Winnefeld, J. and Frank, K., Unmanned Systems Integrated Roadmap. (Department of Defense, USA, 2013).Google Scholar
2. Matveev, A. S., Wang, C. and Savkin, A. V., “Real-time navigation of mobile robots in problems of border patrolling and avoiding collisions with moving and deforming obstacles,” Robot. Auton. Syst. 60 (6), 769–788 (2012).CrossRefGoogle Scholar
3. Savkin, A. V. and Wang, C., “A simple biologically inspired algorithm for collision-free navigation of a unicycle-like robot in dynamic environments with moving obstacles,” Robotica, vol. 31, pp. 993–1001, 2013.CrossRefGoogle Scholar
4. Hoy, M. C., Matveev, A. S. and Savkin, A. V., “Algorithms for collision-free navigation of mobile robots in complex cluttered environments: A survey,” Robotica 33 (3), 463–497 (2015).CrossRefGoogle Scholar
5. Matveev, A. S., Savkin, A. V., Hoy, M. C. and Wang, C., Safe Robot Navigation among Moving and Steady Obstacles (Elsevier, 2015).Google Scholar
6. Savkin, A. V. and Wang, C., “Seeking a path through the crowd: Robot navigation in unknown dynamic environments with moving obstacles based on an integrated environment representation,” Robot. Auton. Syst. 62 (10), 1568–1580 (2014).CrossRefGoogle Scholar
7. Hernandez, J. D., Vidal, E., Vallicrosa, G., Galceran, E. and Carreras, M., “Online Path Planning for Autonomous Underwater Vehicles in Unknown Environments,” Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Seattle, USA (May 2015) pp. 1152–1157.CrossRefGoogle Scholar
8. Subramanian, S., George, T. and Thondiyath, A., “Real-time obstacle avoidance for an underactuated flat-fish type autonomous underwater vehicle in 3D space,” Int. J. Robot. Autom. 29 (4), 424–431 (2014).Google Scholar
9. Munoz, F., Espinoza, E., Gonzalez, I., Carrillo, L. Garcia, Salazar, S. and Lozano, R., “A UAS Obstacle Avoidance Strategy Based on Spiral Trajectory Tracking,” Proceedings of the International Conference on Unmanned Aircraft Systems, Arlington, USA (Jun. 2015) pp. 593–600.CrossRefGoogle Scholar
10. Stastny, T. J., Garcia, G. A. and Keshmiri, S. S., “Collision and obstacle avoidance in unmanned aerial systems using morphing potential field navigation and nonlinear model predictive control,” J. Dyn. Syst. Meas. Control 137 (1), 014503 (2015).CrossRefGoogle Scholar
11. Brockers, R., Kuwata, Y., Weiss, S. and Matthies, L., “Micro Air Vehicle Autonomous Obstacle Avoidance From Stereo-Vision,” Proceedings of SPIE Vol. 9084, Unmanned Systems Technology XVI (Jun. 2014) pp. 90 840O–1–90 840O–12.CrossRefGoogle Scholar
12. Hrabar, S., “Reactive Obstacle Avoidance for Rotorcraft UAVs,” Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, San Francisco, USA (Sep. 2011) pp. 4967–4974.CrossRefGoogle Scholar
13. Hrabar, S., “An evaluation of stereo and laser-based range sensing for rotorcraft unmanned aerial vehicle obstacle avoidance,” J. Field Robot. 29 (2), 215–239 (2012).CrossRefGoogle Scholar
14. Yang, X., Alvarez, L. M. and Bruggemann, T., “A 3D collision avoidance strategy for UAVs in a non-cooperative environment,” J. Intell. Robot. Syst. 70 (1–4), 315–327 (2013).CrossRefGoogle Scholar
15. Shim, D. H. and Sastry, S., “An Evasive Maneuvering Algorithm for UAVs in See-and-Avoid Situations,” American Control Conference, IEEE (2007) pp. 3886–3891.Google Scholar
16. Peng, Z., Wang, D., Shi, Y., Wang, H. and Wang, W., “Containment control of networked autonomous underwater vehicles with model uncertainty and ocean disturbances guided by multiple leaders,” Inform. Sci. 316, 163–179 (2015).CrossRefGoogle Scholar
17. Peng, Z., Wang, D., Chen, Z., Hu, X. and Lan, W., “Adaptive dynamic surface control for formations of autonomous surface vehicles with uncertain dynamics,” IEEE Trans. Control Syst. Technol. 21 (2), 513–520 (2013).CrossRefGoogle Scholar
18. Matveev, A. S., Hoy, M. C. and Savkin, A. V., “3D environmental extremum seeking navigation of a nonholonomic mobile robot,” Automatica 50 (7), 1802–1815 (2014).CrossRefGoogle Scholar
19. Utkin, V. I., Sliding Modes in Control Optimization. (Springer-Verlag, Berlin, 1992).CrossRefGoogle Scholar
20. Offical Website for Parrot ARDrone. [Online]. Available: http://ardrone2.parrot.com/ (Jun., 2015)Google Scholar
21. ROS Driver for Parrot AR-Drone 1.0 and 2.0 Quadrocopters. [Online]. Available: https://github.com/AutonomyLab/ardrone_autonomy (Jun., 2015)Google Scholar
22. ARDrone Aag Follow. [Online]. Available: https://github.com/krishnavamshi/ardrone_tagfollow (Jun., 2015)Google Scholar
23. Control for the Parrot AR Drone. [Online]. Available: https://github.com/gigasquid/clj-drone (Jun., 2015)Google Scholar