Cover Image

Assessment of Collision Avoidance Strategies for an Underwater Transportation System

Faheem Ur Rehman, Enrico Anderlini, Giles Thomas

Abstract


Transportation using multiple autonomous vehicles with detection avoidance capability is useful for military applications. It is important for such systems to avoid collisions with underwater obstacles in an effective way, while keeping track of the target location. In this paper, sensor-based and path-planning methods of external collision avoidance were investigated for an underwater transportation system. In particular, sensor-based wall-following and hard-switching collision avoidance strategies and an offline RRT* path-planning method was implemented on the simulation model of the transportation system of four Hovering Autonomous Underwater Vehicles (HAUVs). Time-domain motion simulations were performed with each method and their ability to avoid obstacles was compared. The hard-switching method resulted in high yaw moments which caused the vehicle to travel towards the goal by a longer distance. Conversely, in the wall-following method, the yaw moment was kept to zero. Moreover, the wall-following method was found to be better than the hard-switching method in terms of time and power efficiency. The comparison between the offline RRT* path-planning and wall-following methods showed that the fuel efficiency of the former is higher whilst its time efficiency is poorer. The major drawback of RRT* is that it can only avoid the previously known obstacles. In future, offline RRT* and wall following can be blended for a better solution. The outcome of this paper provides guidance for the selection of the most appropriate method for collision avoidance for an underwater transportation system.

Keywords


Autonomous Underwater Vehicle (AUV); underwater transportation; multi vehicles; sensor-based methods; path planning method; PID controller

Full Text:

PDF

References


R. Wernli, “Low Cost UUV’s for Military Applications: Is the Technology Ready?,” San Diego, 2000.

K. Alam, T. Ray, and S. G. Anavatti, “Design and construction of an autonomous underwater vehicle,” Neurocomputing, vol. 142, pp. 16–29, 2014.

N. M. Puzai, A. F. Ayob, and M. R. Arshad, “A Review on Recent Advancements in Unmanned Underwater Vehicle Design,” J. Ocean. Mech. Aerosp. - Sci. Eng., vol. 31, pp. 1–8, 2016.

W. H. Wang, X. Q. Chen, A. Marburg, J. G. Chase, and C. E. Hann, “Design of Low-Cost Unmanned Underwater Vehicle for Shallow Waters,” in IEEE/ASME International Conference on Mechatronic and Embedded Systems and Applications, 2008, pp. 204–209.

C. D. Williams, “AUV systems research at the NRC-IOT: An update,” Int. Symp. Underw. Technol., pp. 59–73, 2004.

D. J. Stilwell and B. E. Bishop, “Platoons of Underwater Vehicles,” IEEE Control Syst. Mag., pp. 45–52, 2000.

X. Xiang, B. Jouvencel, and O. Parodi, “Coordinated formation control of multiple autonomous underwater vehicles for pipeline inspection,” Int. J. Adv. Robot. Syst., vol. 7, no. 1, pp. 75–84, 2010.

J. Ghommam, H. Mehrjerdi, M. Saad, and F. Mnif, “Formation path following control of unicycle-type mobile robots,” Rob. Auton. Syst., vol. 58, no. 5, pp. 727–736, 2010.

F. U. Rehman, G. Thomas, and E. Anderlini, “Centralized Control System Design for Underwater Transportation using two Hovering Autonomous Underwater Vehicles (HAUVs),” in IFAC-PapersOnLine, 2019, vol. 52, no. 11, pp. 13–18.

K. Al-Mutib, F. Abdessemed, M. Faisal, H. Ramdane, M. Alsulaiman, and M. Bencherif, “Obstacle Avoidance Using Wall-Following Strategy for Indoor Mobile Robots,” in 2nd IEEE International Symposium on Robotics and Manufacturing Automation (ROMA), 2016.

Y. Liu and R. Bucknall, “Path planning algorithm for unmanned surface vehicle formations in a practical maritime environment,” Ocean Eng., vol. 97, pp. 126–144, 2015.

H. Lee, H. Kim, and H. J. Kim, “Planning and Control for Collision-Free Cooperative Aerial Transportation,” IEEE Trans. Autom. Sci. Eng., vol. 15, no. 1, pp. 189–201, 2018.

R. Song, Y. Liu, and R. Bucknall, “A multi-layered fast marching method for unmanned surface vehicle path planning in a time-variant maritime environment,” Ocean Eng., vol. 129, pp. 301–317, 2017.

Z. Shiller, “Off-Line and On-Line Trajectory Planning,” in Motion and Operation Planning of Robotics Systems, G. Carbone and F. Gomez-Bravo, Eds. Springer, Cham, 2015, pp. 29–62.

E. Lalish and K. A. Morgansen, “Decentralized reactive collision avoidance for multivehicle systems,” in IEEE Conference on Decision and Control, 2008, pp. 1218–1224.

J. L. Fernández, R. Sanz, J. A. Benayas, and A. R. Diéguez, “Improving collision avoidance for mobile robots in partially known environments: The beam curvature method,” Rob. Auton. Syst., vol. 46, pp. 205–219, 2004.

Y. Yoon, J. Shin, H. J. Kim, Y. Park, and S. Sastry, “Model-predictive active steering and obstacle avoidance for autonomous ground vehicles,” Control Eng. Pract., vol. 17, no. 7, pp. 741–750, 2009.

Q. Li and Z. P. Jiang, “Formation tracking control of unicycle teams with collision avoidance,” in 47th IEEE Conference on Decision and Control, 2008, pp. 496–501.

N. Isoda, K. Kogiso, and T. Asai, “Switching strategies of collision avoidance and tracking control for vehicles based on non-cooperative game and model predictive control,” 22nd IEEE Int. Symp. Intell. Control, pp. 178–183, 2007.

K. Kogiso, M. Nogochi, K. Hatada, N. Kida, N. Hirade, and K. Sugimoto, “Experimental Validation of Switching Strategy for Tracking Control with Collision Avoidance in Non-Cooperative Situation Using Toy Model Cars,” SICE J. Control. Meas. Syst. Integr., vol. 3, no. 4, pp. 229–236, 2010.

T. Weerakoon, “Artificial Potential Field and Feature Extraction Method for Mobile Robot Path Planning in Structured Environments,” Kyushu Institute of Technology, 2016.

R. Song, W. Liu, Y. Liu, and R. Bucknall, “A two-layered fast marching path planning algorithm for an unmanned surface vehicle operating in a dynamic environment,” Ocean. - Genova, pp. 1–8, 2015.

O. Grefstad and I. Schjolberg, “Navigation and collision avoidance of underwater vehicles using sonar data,” in 2018 IEEE/OES Autonomous Underwater Vehicle Workshop, 2018, pp. 1–6.

C. S. Tan, “A Collision Avoidance System for Autonomous Underwater Vehicles,” University of Plymouth, 2006.

F. U. Rehman, E. Anderlini, and G. Thomas, “The Impact of Sea Current on Underwater Transportation using Four AUVs,” in International Conference on Autonomous Ships, 2020, pp. 49–58.

J. S. Beggs, Kinematics. Taylors & Francis, 1983.

T. I. Fossen, Handbook of Marine Craft Hydrodynamics and Motion Control, 1st Ed. Sussex: John Wiley & sons, 2011.

S. M. Mo, “Development of a Simulation Platform for ROV systems,” Marine Technology Master Thesis, Norwegian University of Science and Technology, 2015.

F. U. Rehman, G. Thomas, and E. Anderlini, “Development of a Simulation Platform for Underwater Transportation using two Hovering Autonomous Underwater Vehicles (HAUVs),” in Proceedings of the 6th International Conference of Control, Dynamic Systems, and Robotics (CDSR’19), 2019, pp. 1–8.

N. Farr, “Underwater acoustic/optical communications and data connectivity,” Woods Hole Oceanographic Institution (WHOI). 2018.

J. Lloret, S. Sendra, M. Ardid, and J. Rodrigues, “Underwater Wireless Sensor Communications in the 2.4 GHz ISM Frequency Band,” Sensors (Basel), vol. 12, no. 4, pp. 4237–4264, 2012.

M. Li, S. Guo, J. Guo, H. Hirata, and H. Ishihara, “Development of a biomimetic underwater microrobot for a father – son robot system,” Microsyst. Technol., vol. 23, no. 4, pp. 849–861, 2017.

M. Egerstedt, “the control of mobile robots,” 2018. [Online]. Available: https://www.coursera.org/learn/mobile-robot.

I. Noreen, A. Khan, and Z. Habib, “A Comparison of RRT, RRT* and RRT*-Smart Path Planning Algorithms,” Int. J. Comput. Sci. Netw. Secur., vol. 16, no. 10, pp. 20–27, 2016.

S. Karaman and E. Frazzoli, “Incremental sampling-based algorithms for optimal motion planning,” Robot. Sci. Syst., vol. 6, pp. 267–274, 2011.

S. LaValle, “Rapidly-Exploring Random Trees: A New Tool for Path Planning,” 1998.

S. Karaman and E. Frazzoli, “Sampling-based algorithms for optimal motion planning,” Int. J. Rob. Res., vol. 30, no. 7, pp. 846–894, 2011.

J. Nasir et al., “RRT*-SMART: A rapid convergence implementation of RRT*,” Int. J. Adv. Robot. Syst., vol. 10, 2013.

T. Elmokadem, M. Zribi, and K. Youcef-Toumi, “Terminal sliding mode control for the trajectory tracking of underactuated Autonomous Underwater Vehicles,” Ocean Eng., vol. 129, pp. 613–625, 2017.

D. H. Salunkhe, S. Sharma, S. A. Topno, C. Darapaneni, A. Kankane, and S. V. Shah, “Design, Trajectory Generation and Control of Quadrotor Research Platform,” in International Conference on Robotics and Automation for Humanitarian Applications, 2016, pp. 1–7.

D. Mellinger and V. Kumar, “Minimum Snap Trajectory Generation and Control for Quadrotors,” pp. 2520–2525, 2011.

D. Mellinger, “Trajectory Generation and Control for Quadrotors,” Mechanical Engineering and Applied Mechanics PhD Thesis, University of Pennsylvania, 2012.

E. Anderlini, G. G. Parker, and G. Thomas, “Control of a ROV carrying an object,” Ocean Eng., vol. 165, no. March, pp. 307–318, 2018.




DOI: https://doi.org/10.18196/jrc.25112

Article Metrics

Abstract view : 136 times
PDF - 96 times

Refbacks

  • There are currently no refbacks.


Copyright (c) 2020 Journal of Robotics and Control (JRC)

Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.


Abstracted/Indexed by:

    

    

 


Journal of Robotics and Controls (JRC)

P-ISSN: 2715-5056 || E-ISSN: 2715-5072
Organized by Lembaga Penelitian, Publikasi & Pengabdian Masyarakat UMY, Yogyakarta, Indonesia
Published by Universitas Muhammadiyah Yogyakarta, Yogyakarta, Indonesia
Website: http://journal.umy.ac.id/index.php/jrc
Email: jrc@umy.ac.id || jrcofumy@gmail.com


 

Creative Commons License

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.