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Article

A survey of formation control and motion planning of multiple unmanned vehicles

  • Yuanchang Liu (a1) and Richard Bucknall (a1)
Summary

The increasing deployment of multiple unmanned vehicles systems has generated large research interest in recent decades. This paper therefore provides a detailed survey to review a range of techniques related to the operation of multi-vehicle systems in different environmental domains, including land based, aerospace and marine with the specific focuses placed on formation control and cooperative motion planning. Differing from other related papers, this paper pays a special attention to the collision avoidance problem and specifically discusses and reviews those methods that adopt flexible formation shape to achieve collision avoidance for multi-vehicle systems. In the conclusions, some open research areas with suggested technologies have been proposed to facilitate the future research development.

Copyright
COPYRIGHT: © Cambridge University Press 2018 
Corresponding author
*Corresponding author. E-mail: yuanchang.liu.10@ucl.ac.uk
References
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1. US Military, Unmanned System Integrated Roadmap, FY2011-2036. Technical report, US Department of Defense (DoD), 2011.
2. Royal Navy, UNMANNED WARRIOR, year = 2016, url = https://www.royalnavy.mod.uk/news-and-latest-activity/operations/uk-home-waters/unmanned-warrior”, Accessed: 2017-11-08.
3. Zhang, Y. and Mehrjerdi, H., “A Survey on Multiple Unmanned Vehicles Formation Control and Coordination: Normal and Fault Situations,” Proceedings of the International Conference on Unmanned Aircraft Systems (ICUAS), IEEE (2013) pp. 1087–1096.
4. Matthies, L., Kelly, A., Litwin, T. and Tharp, G., “Obstacle Detection for Unmanned Ground Vehicles: A Progress Report,” In: Robotics Research (Giralt, G. and Hirzinger, G., eds.) (Springer 1996) pp. 475–486.
5. Manley, J. E., “Unmanned Surface Vehicles, 15 Years of Development,” Proceedings of the OCEANS, IEEE (2008) pp. 1–4.
6. Oh, K.-K., Park, M.-C. and Ahn, H.-S., “A survey of multi-agent formation control,” Automatica 53, 424–440 (2015).
7. Bellingham, J. S., Tillerson, M., Alighanbari, M. and How, J. P., “Cooperative Path Planning for Multiple Uavs in Dynamic and Uncertain Environments,” Proceedings of the 41st IEEE Conference on Decision and Control, volume 3, IEEE (2002) pp. 2816–2822.
8. Tsourdos, A., White, B. and Shanmugavel, M., Cooperative Path Planning of Unmanned Aerial Vehicles, volume 32 (John Wiley & Sons, The Atrium, United Kingdom, 2010).
9. Egerstedt, M. and Hu, X., “Formation constrained multi-agent control,” IEEE Trans. Robot. Autom. 17 (6), 947–951 (2001).
10. Garrido, S., Moreno, L. and Lima, P. U., “Robot formation motion planning using fast marching,” Robot. Auton. Syst. 59 (9), 675–683 (2011).
11. Gómez, J. V., Lumbier, A., Garrido, S. and Moreno, L., “Planning robot formations with fast marching square including uncertainty conditions,” Robot. Auton. Syst. 61 (2), 137–152 (2013).
12. Stone, P. and Veloso, M., “Multiagent systems: A survey from a machine learning perspective,” Auton. Robots 8 (3), 345–383 (2000).
13. Scharf, D. P., Hadaegh, F. Y. and Ploen, S. R., “A Survey of Spacecraft Formation Flying Guidance and Control. Part II: Control,” Proceedings of the American Control Conference, volume 4, IEEE (2004) pp. 2976–2985.
14. Ren, W., Beard, R. W. and Atkins, E. M., “A Survey of Consensus Problems in Multi-Agent Coordination,” Proceedings of the American Control Conference, IEEE (2005) pp. 1859–1864.
15. Tam, C. K., Motion Planning Algorithm for Ships in Close Range Encounters. Ph.D. Thesis, UCL (University College London, 2009).
16. Campbell, S., Naeem, W. and Irwin, G. W., “A review on improving the autonomy of unmanned surface vehicles through intelligent collision avoidance manoeuvres,” Annu. Rev. Control 36 (2), 267–283 (2012).
17. Elbanhawi, M. and Simic, M., “Sampling-based robot motion planning: A review,” IEEE Access 2, 56–77 (2014).
18. Goerzen, C., Kong, Z. and Mettler, B., “A survey of motion planning algorithms from the perspective of autonomous uav guidance,” J. Intell. Robot. Syst. 57 (1–4), 65 (2010).
19. Chandler, P. R., Pachter, M. and Rasmussen, S., “UAV Cooperative Control,” Proceedings of the 2001 American Control Conference, volume 1, IEEE, (2001), pp. 50–55.
20. Fukuda, T. and Nakagawa, S., “Dynamically Reconfigurable Robotic System,” Proceedings of the IEEE International Conference on Robotics and Automation, IEEE (1988) pp. 1581–1586.
21. Asama, H., Matsumoto, A. and Ishida, Y., “Design of an Autonomous and Distributed Robot System: Actress,” Proceedings of the IEEE/RSJ IROS (1989) pp. 283–290.
22. Balakirsky, S., Carpin, S., Kleiner, A., Lewis, M., Visser, A., Wang, J. and Ziparo, V. A., “Towards heterogeneous robot teams for disaster mitigation: Results and performance metrics from robocup rescue,” J. Field Robot. 24 (11–12), 943–967 (2007).
23. Liu, Y. and Nejat, G., “Multirobot cooperative learning for semiautonomous control in urban search and rescue applications,” J. Field Robot. 33 (4), 512–536 (2016).
24. Guzman, R., Navarro, R., Ferre, J. and Moreno, M., “Rescuer: Development of a modular chemical, biological, radiological, and nuclear robot for intervention, sampling, and situation awareness,” J. Field Robot. 33 (7), 931–945 (2016).
25. Nagatani, K. et al, “Multirobot exploration for search and rescue missions: A report on map building in robocuprescue 2009,” J. Field Robot. 28 (3), 373–387 (2011).
26. Saeedi, S., Trentini, M., Seto, M. and Li, H., “Multiple-robot simultaneous localization and mapping: A review,” J. Field Robot. 33 (1), 3–46 (2016).
27. Girard, A. R., Howell, A. S. and Hedrick, J. K., “Border Patrol and Surveillance Missions using Multiple Unmanned Air Vehicles,” Proceedings of the43rd IEEE Conference on Decision and Control, volume 1, IEEE (2004) pp. 620–625.
28. Roehr, T. M., Cordes, F. and Kirchner, F., “Reconfigurable integrated multirobot exploration system (RIMRES): Heterogeneous modular reconfigurable robots for space exploration,” J. Field Robot. 31 (1), 3–34 (2014).
29. Breivik, M. and Hovstein, V. E., “Formation Control for Unmanned Surface Vehicles: Theory and Practice,” Proceedings of the IFAC World Congress (2008).
30. Liu, Y. and Bucknall, R., “Path planning algorithm for unmanned surface vehicle formations in a practical maritime environment,” Ocean Eng. 97, 126–144 (2015).
31. Shanmugavel, M., Tsourdos, A., White, B. and Zbikowski, R., “Co-operative path planning of multiple UAVs using dubins paths with clothoid arcs,” Control Eng. Pract. 18 (9), 1084–1092 (2010).
32. Cui, R., Guo, J. and Gao, B., “Game theory-based negotiation for multiple robots task allocation,” Robotica 31 (06), 923–934 (2013).
33. Gerkey, B. P. and Matarić, M. J., “A formal analysis and taxonomy of task allocation in multi-robot systems,” Int. J. Robot. Res. 23 (9), 939–954 (2004).
34. Khamis, A., Hussein, A. and Elmogy, A., “Multi-Robot Task Allocation: A Review of the State-of-the-Art,” In: Cooperative Robots and Sensor Networks 2015 (Koubâa, A., Ramiro, J. and Dios, Martínez-de, eds.) (Springer, Switzerland, 2015) pp. 31–51.
35. Zhu, D., Huang, H. and Yang, S. X., “Dynamic task assignment and path planning of multi-auv system based on an improved self-organizing map and velocity synthesis method in three-dimensional underwater workspace,” IEEE Trans. Cybern. 43 (2), 504–514 (2013).
36. Faigl, J. and Hollinger, G. A., “Autonomous data collection using a self-organizing map,” IEEE Trans. Neural Netw. Learning Syst. PP(99), 1–13 (2017).
37. Liu, Y. and Bucknall, R., “Efficient multi-task allocation and path planning for unmanned surface vehicle in support of ocean operations,” Neurocomputing 275: 1550–1566 (2018).
38. Muñoz, P., R-Moreno, M. D. and Barrero, D. F., “Unified framework for path-planning and task-planning for autonomous robots,” Robot. Auton. Syst. 82, 1–14 (2016).
39. Mahmoud Zadeh, S., Powers, D. M. W., Sammut, K. and Yazdani, A., “Toward efficient task assignment and motion planning for large-scale underwater missions,” Int. J. Adv. Robot. Syst. 13 (5)(2016), Art. no. 1729881416657974.
40. Zhu, D., Cao, X., Sun, B. and Luo, C., “Biologically inspired self-organizing map applied to task assignment and path planning of an auv system,” IEEE Trans. Cogn. Develop. Syst. PP(99), 1–11 (2017).
41. Dong, X., Zhou, Y., Ren, Z. and Zhong, Y., “Time-varying formation control for unmanned aerial vehicles with switching interaction topologies,” Control Eng. Pract. 46, 26–36 (2016).
42. Yamchi, M. H. and Esfanjani, R. M., “Distributed predictive formation control of networked mobile robots subject to communication delay,” Robot. Auton. Syst. 91, 194–207 (2017).
43. Li, H., Xie, P. and Yan, W., “Receding horizon formation tracking control of constrained underactuated autonomous underwater vehicles,” IEEE Trans. Ind. Electron. 64 (6), 5004–5013 (2017).
44. Chen, Y. Q. and Wang, Z., “Formation Control: A Review and A New Consideration,” Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, IEEE (2005) pp. 3181–3186.
45. Wang, P. K. C., “Navigation strategies for multiple autonomous mobile robots moving in formation,” J. Robot. Syst. 8 (2), 177–195 (1991).
46. Yang, T., Liu, Z., Chen, H. and Pei, R., “Formation control of mobile robots: State and open problems,” Zhineng Xitong Xuebao (CAAI Trans. Intell. Syst.) 2 (4), 21–27 (2007).
47. Peng, Z., Wen, G., Rahmani, A. and Yu, Y., “Leader–follower formation control of nonholonomic mobile robots based on a bioinspired neurodynamic based approach,” Robot. Auton. Syst. 61 (9), 988–996 (2013).
48. Desai, J. P., Ostrowski, J. and Kumar, V., “Controlling Formations of Multiple Mobile Robots,” Proceedings of the IEEE International Conference on Robotics and Automation, volume 4, IEEE (1998) pp. 2864–2869.
49. Consolini, L., Morbidi, F., Prattichizzo, D. and Tosques, M., “Leader–follower formation control of nonholonomic mobile robots with input constraints,” Automatica 44 (5), 1343–1349 (2008).
50. Edwards, D. B., Bean, T. A., Odell, D. L. and Anderson, M. J., “A leader-follower algorithm for multiple AUV formations,” IEEE/OES Autonomous Underwater Vehicles (IEEE Cat. No.04CH37578), 2004, pp. 40–46.
51. Orqueda, O. A. A., Zhang, X. T. and Fierro, R., “An output feedback nonlinear decentralized controller for unmanned vehicle co-ordination,” Int. J. Robust Nonlinear Control 17 (12), 1106–1128 (2007).
52. Peng, Z., Wang, D., Lan, W. and Sun, G., “Robust leader-follower formation tracking control of multiple underactuated surface vessels,” China Ocean Eng. 26, 521–534 (2012).
53. Tan, K.-H. and Lewis, M. A., “Virtual Structures for High-Precision Cooperative Mobile Robotic Control,” Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems' 96, volume 1, IEEE (1996) pp. 132–139.
54. Lewis, M. A. and Tan, K.-H., “High precision formation control of mobile robots using virtual structures,” Auton. Robots 4 (4), 387–403 (1997).
55. Do, K. D., “Bounded controllers for formation stabilization of mobile agents with limited sensing ranges,” IEEE Trans. Autom. Control 52 (3), 569–576 (2007).
56. Do, K. D., “Formation control of multiple elliptical agents with limited sensing ranges,” Automatica 48 (7), 1330–1338 (2012).
57. Balch, T. and Arkin, R. C., “Behavior-based formation control for multirobot teams,” IEEE Trans. Robot. Autom. 14 (6), 926–939 (1998).
58. Do, K. D. and Pan, J., “Nonlinear formation control of unicycle-type mobile robots,” Robot. Auton. Syst. 55 (3), 191–204 (2007).
59. Cao, Z., Tan, M., Wang, S., Fan, Y. and Zhang, B., “The Optimization Research of Formation Control for Multiple Mobile Robots,” Proceedings of the 4th World Congress on Intelligent Control and Automation, volume 2, IEEE (2002) pp. 1270–1274.
60. Cao, Z., Xie, L., Zhang, B., Wang, S. and Tan, M., “Formation Constrained Multi-Robot System in Unknown Environments,” Proceedings of the IEEE International Conference on Robotics and Automation, volume 1, IEEE (2003) pp. 735–740.
61. Yang, F., Liu, F., Liu, S. and Zhong, C., “Hybrid Formation Control of Multiple Mobile Robots with Obstacle Avoidance,” Proceedings of the 8th World Congress on Intelligent Control and Automation (WCICA), IEEE (2010) pp. 1039–1044.
62. Forsyth, D. R. and Elliott, T. R., “Group dynamics and psychological well-being: The impact of groups on adjustment and dysfunction,” In: The social psychology of emotional and behavioral problems: Interfaces of social and clinical psychology (Kowalski, R. M. and Leary, M. R., eds.), (1999) pp. 339–361.
63. Tousi, M. M., Aghdam, A. G. and Khorasani, K., “A Hybrid Fault Diagnosis and Recovery for a Team of Unmanned Vehicles,” Proceedings of the IEEE International Conference on System of Systems Engineering, IEEE (2008) pp. 1–6.
64. Yang, H., Staroswiecki, M., Jiang, B. and Liu, J., “Fault tolerant cooperative control for a class of nonlinear multi-agent systems,” Syst. Control Lett. 60 (4), 271–277 (2011).
65. Tousi, M. M. and Khorasani, K., “Optimal hybrid fault recovery in a team of unmanned aerial vehicles,” Automatica 48 (2), 410–418 (2012).
66. Tam, C., Bucknall, R. and Greig, A., “Review of collision avoidance and path planning methods for ships in close range encounters,” J. Navig. 62 (03), 455–476 (2009).
67. Korf, R. E., “Real-time heuristic search,” Artif. Intell. 42 (2), 189–211 (1990).
68. Tam, C. and Bucknall, R., “Cooperative path planning algorithm for marine surface vessels,” Ocean Eng. 57, 25–33 (2013).
69. Sharma, S., Sutton, R., Hatton, D. and Singh, Y., “Path Planning of an Autonomous Surface Vehicle Based on Artificial Potential Fields in a Real Time Marine Environment,” Proceedings of the 16th Conference on Computer and IT Application in the Maritime Industries (2017) pp. 48–54.
70. Khatib, O., “Real-time obstacle avoidance for manipulators and mobile robots,” Int. J. Robot. Res. 5 (1), 90–98 (1986).
71. Lee, S.-M., Kwon, K.-Y. and Joh, J., “A fuzzy logic for autonomous navigation of marine vehicles satisfying colreg guidelines,” Int. J. Control Autom. Syst. 2 (2), 171–181 (2004).
72. Wang, J., Wu, X. and Xu, Z., “Potential-based obstacle avoidance in formation control,” J. Control Theory Appl. 6 (3), 311–316 (2008).
73. Paul, T., Krogstad, T. R. and Gravdahl, J. T., “Modelling of UAV formation flight using 3D potential field,” Simul. Model. Pract. Theor. 16 (9), 1453–1462 (2008).
74. Yang, Y., Wang, S., Wu, Z. and Wang, Y., “Motion planning for multi-HUG formation in an environment with obstacles,” Ocean Eng. 38 (17), 2262–2269 (2011).
75. Kim, J.-O. and Khosla, P. K., “Real-time obstacle avoidance using harmonic potential functions,” IEEE Trans. Robot. Autom. 8 (3), 338–349 (1992).
76. Masoud, S. et al, “Motion planning in the presence of directional and regional avoidance constraints using nonlinear, anisotropic, harmonic potential fields: A physical metaphor,” IEEE Trans. Syst. Man Cybern., Part A: Syst. Humans 32 (6), 705–723 (2002).
77. Connolly, C. I., Burns, J. B. and Weiss, R., “Path Planning using Laplace's Equation,” Proceedings of the IEEE International Conference on Robotics and Automation, IEEE (1990) pp. 2102–2106.
78. Daily, R. and Bevly, David M, “Harmonic Potential Field Path Planning for High Speed Vehicles,” Proceedings of the American Control Conference, IEEE (2008) pp. 4609–4614.
79. Zheng, C., Ding, M., Zhou, C. and Li, L., “Coevolving and cooperating path planner for multiple unmanned air vehicles,” Eng. Appl. Artif. Intell. 17 (8), 887–896 (2004).
80. Kala, R., “Multi-robot path planning using co-evolutionary genetic programming,” Expert Syst. Appli. 39 (3), 3817–3831 (2012).
81. Qu, H., Xing, K. and Alexander, T., “An improved genetic algorithm with co-evolutionary strategy for global path planning of multiple mobile robots,” Neurocomputing 120, 509–517 (2013).
82. Kendoul, F., “Survey of advances in guidance, navigation, and control of unmanned rotorcraft systems,” J. Field Robot. 29 (2), 315–378 (2012).
83. Schouwenaars, T., How, J. and Feron, E., “Receding Horizon Path Planning with Implicit Safety Guarantees,” Proceedings of the American Control Conference, volume 6, IEEE (2004) pp. 5576–5581.
84. Yilmaz, N. K., Evangelinos, C., Lermusiaux, P. F. J. and Patrikalakis, N. M., “Path planning of autonomous underwater vehicles for adaptive sampling using mixed integer linear programming,” IEEE J. Ocean. Eng. 33 (4), 522–537 (2008).
85. Bemporad, A. and Rocchi, C., “Decentralized Linear Time-Varying Model Predictive Control of a Formation of Unmanned Aerial Vehicles,” Proceedings ofthe 50th IEEE Conference on Decision and Control and European Control Conference (CDC-ECC), IEEE (2011) pp. 7488–7493.
86. Chen, Y., Yu, J., Su, X. and Luo, G., “Path planning for multi-UAV formation,” J. Intell. Robot. Syst. 77 (1), 229–246 (2015).
87. Nishitani, I., Matsumura, T., Ozawa, M., Yorozu, A. and Takahashi, M., “Human-centered X-Y–T space path planning for mobile robot in dynamic environments,” Robot. Auton. Syst. 66, 18–26 (2015).
88. Dakulović, M. and Petrović, I., “Two-way D star algorithm for path planning and replanning,” Robot. Auton. Syst. 59 (5), 329–342 (2011).
89. Cagigas, D., “Hierarchical D star algorithm with materialization of costs for robot path planning,” Robot. Auton. Syst. 52 (2), 190–208 (2005).
90. Rashid, A. T., Ali, A. A., Frasca, M. and Fortuna, L., “Path planning with obstacle avoidance based on visibility binary tree algorithm,” Robot. Auton. Syst. 61 (12), 1440–1449 (2013).
91. Qureshi, A. H. and Ayaz, Y., “Intelligent bidirectional rapidly-exploring random trees for optimal motion planning in complex cluttered environments,” Robot. Auton. Syst. 68, 1–11 (2015).
92. Jaillet, L., Cortés, J. and Siméon, T., “Sampling-based path planning on configuration-space costmaps,” IEEE Trans. Robot. 26 (4), 635–646 (2010).
93. Van Den Berg, J., Abbeel, P. and Goldberg, K., “Lqg-mp: Optimized path planning for robots with motion uncertainty and imperfect state information,” Int. J. Robot. Res. 30 (7), 895–913 (2011).
94. Garrido, S., Malfaz, M. and Blanco, D., “Application of the fast marching method for outdoor motion planning in robotics,” Robot. Auton. Syst. 61 (2), 106–114 (2013).
95. Yao, M. and Zhao, M., “Unmanned aerial vehicle dynamic path planning in an uncertain environment,” Robotica 33 (03), 611–621 (2015).
96. Donald, B., Xavier, P., Canny, J. and Reif, J., “Kinodynamic motion planning,” J. ACM 40 (5), 1048–1066 (1993).
97. LaValle, S. M. and Kuffner, J. J., “Randomized kinodynamic planning,” Int. J. Robot. Res. 20 (5), 378–400 (2001).
98. Hsu, D., Kindel, R., Latombe, J.-C. and Rock, S., “Randomized kinodynamic motion planning with moving obstacles,” Int. J. Robot. Res. 21 (3), 233–255 (2002).
99. Şahin, E., “Swarm Robotics: From Sources of Inspiration to Domains of Application. In International Workshop on Swarm Robotics (Şahin, E. and Spears, W. M., eds.)(Springer, Springer-Verlag, Berlin, Heidelberg, 2005) pp. 10–20.
100. Barca, J. C. and Sekercioglu, Y. A., “Swarm robotics reviewed,” Robotica 31 (3), 345–359 (2013).
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