|Table of Contents|

Citation:
　Runlong Miao,Shuo Pang,Dapeng Jiang.Development of an Inexpensive Decentralized Autonomous Aquatic Craft Swarm System for Ocean Exploration[J].Journal of Marine Science and Application,2019,(3):343-352.[doi:10.1007/s11804-019-00097-3]
Click and Copy

Development of an Inexpensive Decentralized Autonomous Aquatic Craft Swarm System for Ocean Exploration

Info

Title:
Development of an Inexpensive Decentralized Autonomous Aquatic Craft Swarm System for Ocean Exploration
Author(s):
Runlong Miao;  Shuo Pang;  Dapeng Jiang
Affilations:
Author(s):
Runlong Miao;  Shuo Pang;  Dapeng Jiang
National Key Laboratory of Autonomous Underwater Vehicle, College of Shipbuilding Engineering, Harbin Engineering University, Harbin 150001, China
Keywords:
Marine environment monitoring; Swarm robotics; Autonomous aquatic craft; Unmanned surface vehicles; Autonomous aquatic craft swarm system; Decentralized control
分类号:
-
DOI:
10.1007/s11804-019-00097-3
Abstract:
Swarm robotics in maritime engineering is a promising approach characterized by large numbers of relatively small and inexpensive autonomous aquatic crafts (AACs) to monitor marine environments. Compared with a single, large aquatic manned or unmanned surface vehicle, a highly distributed aquatic swarm system with several AACs features advantages in numerous real-world maritime missions, and its natural potential is qualified for new classes of tasks that uniformly feature low cost and high efficiency through time. This article develops an inexpensive AAC based on an embedded-system companion computer and open-source autopilot, providing a verification platform for education and research on swarm algorithm on water surfaces. A topology communication network, including an inner communication network to exchange information among AACs and an external communication network for monitoring the state of the AAC Swarm System (AACSS), was designed based on the topology built into the Xbee units for the AACSS. In the emergence control network, the transmitter and receiver were coupled to distribute or recover the AAC. The swarm motion behaviors in AAC were resolved into the capabilities of go-to-waypoint and path following, which can be accomplished by two uncoupled controllers:speed controller and heading controller. The good performance of velocity and heading controllers in go-to-waypoint was proven in a series of simulations. Path following was achieved by tracking a set of ordered waypoints in the go-to-waypoint. Finally, a sea trial conducted at the China National Deep Sea Center successfully demonstrated the motion capability of the AAC. The sea trial results showed that the AAC is suited to carry out environmental monitoring tasks by efficiently covering the desired path, allowing for redundancy in the data collection process and tolerating the individual AACs’ path-following offset caused by winds and waves.

References:

Ballesteros-Gómez A, Rubio S (2011) Recent advances in environmental analysis. Analytical chemistry 83(12):4579-4613. https://doi.org/10.1021/ac200921j
Brambilla M, Ferrante E, Birattari M, Dorigo M (2013) Swarm robotics:a review from the swarm engineering perspective. Swarm Intelligence 7(1):1-41. https://doi.org/10.1007/s11721-012-0075-2
Castello E, Yamamoto T, Libera FD, Liu W, Winfield AFT, Nakamura Y, Ishiguro H (2016) Adaptive foraging for simulated and real robotic swarms:the dynamical response threshold approach. Swarm Intelligence 10(1):1-31. https://doi.org/10.1007/s11721-015-0117-7
Christensen AL, O’Grady R, Dorigo M (2009) From fireflies to fault tolerant swarms of robots. IEEE Trans Evol Comput 13(4):1-12.https://doi.org/10.1109/TEVC.2009.2017516
Crespi V, Galstyan A, Lerman K (2008) Top-down vs bottom-up methodologies in multi-agent system design. Auton Robot 24(3):303-313. https://doi.org/10.1007/s10514-007-9080-5
Danymol R, Ajitha T, Gandhiraj R (2014) Real-time communication system design using RTL-SDR and Raspberry Pi. International Conference on Advanced Computing and Communication Systems. Coimbatore, India, December 1-5. https://doi.org/10.1109/ICACCS.2013.6938691
Dong X, Zhou Y, Lu G, Zhong Y (2016) Time-varying formation control for unmanned aerial vehicles with switching interaction topologies. Control Eng Pract 46:26-36. https://doi.org/10.1016/j.conengprac.2015.10.001
Duarte M, Gomes J, Costa V, Rodrigues T, Silva F (2016). Application of swarm robotics systems to marine environmental monitoring. Oceans Conference. IEEE, Shanghai, China, April 10-13. https://doi.org/10.1109/OCEANSAP.2016.7485429
Dunbabin M, Marques L (2012) Robots for environmental monitoring:significant advancements and applications. IEEE Robot Autom Mag 19(1):24-39. https://doi.org/10.1109/MRA.2011.2181683
Floreano D, Mitri S, Magnenat S, Keller L (2007) Evolutionary conditions for the emergence of communication in robots. Curr Biol 17(6):514-519. https://doi.org/10.1016/j.cub.2007.01.058
Fossen T (1994) Guidance and control of ocean vehicles. Wiley, New York 133-183
Leonard NE, Paley DA, Davis RE, Fratantoni DM, Lekien F, Zhang F (2010) Coordinated control of an underwater glider fleet in an adaptive ocean sampling field experiment in Monterey bay. J Field Robot 27(6):718-740. https://doi.org/10.1002/rob.20366
Li M, Lu K, Zhu H (2008) Robot swarm communication networks:architectures, protocols, and applications. The Third International Conference on Communications and Networking in China, Hangzhou, China, August 162-166. https://doi.org/10.1109/CHINACOM.2008.4684993
Meier L, Tanskanen P, Heng L, Lee GH, Fraundorfer F, Pollefeys M (2012) PIXHAWK:a micro aerial vehicle design for autonomous flight using onboard computer vision. Autonomous Robotics 33(1-2):21-39. https://doi.org/10.1007/s10514-012-9281-4
Parker CA, Zhang H (2011) Biologically inspired collective comparisons by robotic swarms. The International Journal of Robotics Research 30(5):524-535. https://doi.org/10.1177/0278364910397621
Rosales C, Soria C, Carelli R, Rossomando F (2017) Adaptive dynamic control of a quadrotor for trajectory tracking. In 2017 International Conference on Unmanned Aircraft Systems, Miami, USV, June 547-553. https://doi.org/10.1109/ICUAS.2017.7991492
?ahin E (2004) Swarm robotics:From sources of inspiration to domains of application. International Workshop on Swarm Robotics, Berlin, Genman, July 10-20. https://doi.org/10.1007/978-3-540-30552-1_2
Soysal O, Bahç E (2007) Aggregation in swarm robotic systems:evolution and probabilistic control. Turkish Journal of Electrical Engineering & Computer Sciences 15(2):199-225
Valada A, Velagapudi P, Kannan B, Tomaszewski C, Kantor G, Scerri P (2014) Development of a low cost multi-robot autonomous marine surface platform. Field and Service Robotics 92:643-658. https://doi.org/10.1007/978-3-642-40686-7_43
Wang L, Chu XM, Liu CG (2015) Different drive models of USV under the wind and waves disturbances MPC trajectory tracking simulation research. In 2015 International Conference on Transportation Information and Safety, Wuhan, China, June 563-568 https://doi.org/10.1109/ICTIS.2015.7232199
Wolf MT, Rahmani A, de la Croix JP, Woodward G, Vander Hook J, Brown D, Pomerantz M (2017) CARACaS multi-agent maritime autonomy for unmanned surface vehicles in the Swarm Ⅱ harbor patrol demonstration. In Unmanned Systems Technology XIX, International Society for Optics and Photonics 10195:101950O.https://doi.org/10.1117/12.2262067
Wright RG, Baldauf M (2016) Hydrographic survey in remote regions:Using vessels of opportunity equipped with 3-dimensional forwardlooking sonar. Marine Geodesy 39(6):439-457. https://doi.org/10.1080/01490419.2016.1245226
Xu G, Shen W, Wang X (2014) Applications of wireless sensor networks in marine environment monitoring:A survey. Sensors 14(9):16932-16954. https://doi.org/10.3390/s140916932
Yu Y, Chen X, Lu Z, Li F, Zhang B (2017) Obstacle avoidance behavior of swarm robots based on aggregation and disaggregation method. Simulation Transactions of the Society for Modeling & Simulation International 93(11):885-898. https://doi.org/10.1177/0037549717711281
Zhu B, Xie L, Han D, Meng X, & Teo R (2017) A survey on recent progress in control of swarm systems. Science China Information Sciences 60(7):070201. https://doi.org/10.1007/s11432-016-9088-2

Memo

Memo:
Received date:2018-03-23;Accepted date:2019-01-16。
Corresponding author:Shuo Pang,sspp27@hotmail.com
Last Update: 2019-09-18