journal article·2022-05

Task Planning and Collaboration of Jellyfish-inspired Multiple Spherical Underwater Robots

Ruochen An, Shuxiang Guo, Yuanhua Yu, Chunying Li, Tendeng Awa

Journal of Bionic Engineering· Volume 19· Issue 3
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Abstract

No abstract is available for this record. The assistant can identify its topic from the title, but cannot infer the study’s results.

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Research context

OpenAlex topics: Underwater Vehicles and Communication Systems · Modular Robots and Swarm Intelligence · Distributed Control Multi-Agent Systems

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References (32)

Show source-provided references
1. Li, X., & Zhu, D. Q. (2018). An adaptive SOM neural network method for distributed formation control of a group of AUVs. IEEE Transactions on Industrial Electronics, 65, 8260–8270.
2. Wang, J. W., Chen, K. R., & Lewis, F. L. (2017). Coordination of multi-agent systems on interacting physical and communication topologies. Systems & Control Letters, 100, 56–65.10.1016/j.sysconle.2016.12.008 ↗
3. Yuan, Y. L., Liang, C. C., Kaneko, M., Chen, X., & Hogrefe, D. (2018). Topology control for energy-efficient localization in mobile underwater sensor networks using Stackelberg game. IEEE Transactions on Vehicular Technology, 68, 1487–1500.10.1109/TVT.2018.2886904 ↗
4. Yu, J. Z., Wang, C., & Xie, G. M. (2015). Coordination of multiple robotic fish with applications to underwater robot competition. IEEE Transactions on Industrial Electronics, 63, 1280–1288.10.1109/TIE.2015.2425359 ↗
5. Lee, G., & Chwa, D. (2018). Decentralized behavior-based formation control of multiple robots considering obstacle avoidance. Intelligent Service Robotics, 11, 127–138.10.1007/s11370-017-0240-y ↗
6. Wang, Y., Tang, C., Wang, S., Cheng, L., Wang, R., Tan, M., & Hou, Z. G. (2021). Target tracking control of a biomimetic underwater vehicle through deep reinforcement learning. IEEE Transactions on Neural Networks and Learning Systems. https://doi.org/10.1109/TNNLS.2021.305440210.1109/TNNLS.2021.3054402 ↗
7. He, W., Gao, H. J., Zhou, C., Yang, C. G., & Li, Z. J. (2020). Reinforcement learning control of a flexible two-link manipulator: An experimental investigation. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 51, 7326–7336.10.1109/TSMC.2020.2975232 ↗
8. Sui, Z. Z., Pu, Z. Q., Yi, J. Q., & Wu, S. G. (2020). Formation control with collision avoidance through deep reinforcement learning using model-guided demonstration. IEEE Transactions on Neural Networks and Learning Systems, 32, 2358–2372.10.1109/TNNLS.2020.3004893 ↗
9. Rizk, Y., Awad, M., & Tunstel, E. W. (2018). Decision making in multiagent systems: A survey. IEEE Transactions on Cognitive and Developmental Systems, 10, 514–529.10.1109/TCDS.2018.2840971 ↗
10. Wang, J. Q., Wang, C., Wei, Y. J., & Zhang, C. J. (2019). Neuroadaptive sliding mode formation control of autonomous underwater vehicles with uncertain dynamics. IEEE Systems Journal, 14, 3325–3333.10.1109/JSYST.2019.2938315 ↗
11. Zhai, Y. F., Zheng, X. W., & Xie, G. M. (2021). Fish lateral line inspired flow sensors and flow-aided control: A review. Journal of Bionic Engineering, 18, 264–291.10.1007/s42235-021-0034-y ↗
12. Yu, J. Z., Wang, M., Dong, H. F., Zhang, Y. L., & Wu, Z. X. (2018). Motion control and motion coordination of bionic robotic fish: A review. Journal of Bionic Engineering, 15, 579–598.10.1007/s42235-018-0048-2 ↗
13. Xiao, H. Z., Li, Z. J., & Chen, C. P. (2016). Formation control of leader-follower mobile robots’ systems using model predictive control based on neural-dynamic optimization. IEEE Transactions on Industrial Electronics, 63, 5752–5762.10.1109/TIE.2016.2542788 ↗
14. Long, Y., Du, Z. J., Chen, C. F., Wang, W. D., He, L., Mao, X. W., Xu, G. Q., Zhao, G. Y., Li, X. L., & Dong, W. (2017). Development and analysis of an electrically actuated lower extremity assistive exoskeleton. Journal of Bionic Engineering, 14, 272–283.10.1016/S1672-6529(16)60397-9 ↗
15. Li, G. N., Xu, H. L., & Lin, Y. (2018). Application of bat algorithm based time optimal control in multi-robots formation reconfiguration. Journal of Bionic Engineering, 15, 126–138.10.1007/s42235-017-0010-8 ↗
16. Rao, D. C., Kabat, M. R., Das, P. K., & Jena, P. K. (2019). Hybrid IWD-DE: A novel approach to model cooperative navigation planning for multi-robot in unknown dynamic environment. Journal of Bionic Engineering, 16, 235–252.10.1007/s42235-019-0020-9 ↗
17. Girerd, C., Kudryavtsev, A. V., Rougeot, P., Renaud, P., Rabenorosoa, K., & Tamadazte, B. (2020). SLAM-based follow-the-leader deployment of concentric tube robots. IEEE Robotics and Automation Letters, 5, 548–555.10.1109/LRA.2019.2963821 ↗
18. Gemmell, B. J., Costello, J. H., Colin, S. P., Stewart, C. J., Dabiri, J. O., Tafti, D., & Priya, S. (2013). Passive energy recapture in jellyfish contributes to propulsive advantage over other metazoans. Proceedings of the National Academy of Sciences, 110, 17904–17909.10.1073/pnas.1306983110 ↗
19. Gu, S. X., Guo, S. X., & Zheng, L. (2020). A highly stable and efficient spherical underwater robot with hybrid propulsion devices. Autonomous Robots, 44, 759–771.10.1007/s10514-019-09895-8 ↗
20. Gu, S. X., & Guo, S. X. (2017). Performance evaluation of a novel propulsion system for the spherical underwater robot (SURIII). Applied Sciences, 7, 1196.10.3390/app7111196 ↗
21. Hou, X. H., Guo, S. X., Shi, L. W., Xing, H. M., Yin, H., Li, Z., Zhou, M. G., & Xia, D. B. (2020). Improved model predictive-based underwater trajectory tracking control for the biomimetic spherical robot under constraints. Applied Sciences, 10, 8106.10.3390/app10228106 ↗
22. Guo, J., Li, C. X., & Guo, S. X. (2020). Study on the autonomous multirobot collaborative control system based on spherical amphibious robots. IEEE Systems Journal, 15, 4950–4957.10.1109/JSYST.2020.3023727 ↗
23. An, R. C., Guo, S. X., Gu, S. X., & Zheng, L. (2019). Improvement and evaluation for the stability of mobile spherical underwater robots (SUR III). 2019 IEEE International Conference on Mechatronics and Automation, Tianjin, China, 2512–2517.10.1109/ICMA.2019.8816247 ↗
24. Guo, J., Li, C. X., & Guo, S. X. (2019). A novel step optimal path planning algorithm for the spherical mobile robot based on fuzzy control. IEEE Access, 8, 1394–1405.10.1109/ACCESS.2019.2962074 ↗
25. Xing, H. M., Shi, L. W., Tang, K., Guo, S. X., Hou, X. H., Liu, Y., Liu, H. K., & Hu, Y. (2019). Robust RGB-D camera and IMU fusion-based cooperative and relative close-range localization for multiple turtle-inspired amphibious spherical robots. Journal of Bionic Engineering, 16, 442–454.10.1007/s42235-019-0036-1 ↗
26. Zheng, L., Guo, S. X., & Gu, S. X. (2019). The communication and stability evaluation of amphibious spherical robots. Microsystem Technologies, 25, 2625–2636.10.1007/s00542-018-4223-5 ↗
27. An, R. C., Guo, S. X., Zheng, L., Awa, T., & Sui, W. B. (2020). Modeling and experimental verification of a new spherical underwater robot. 2020 IEEE International Conference on Mechatronics and Automation, Beijing, China, 1222–1227.10.1109/ICMA49215.2020.9233765 ↗
28. Zheng, L., Guo, S. X., Piao, Y., Gu, S. X., & An, R. C. (2020). Collaboration and task planning of turtle-inspired multiple amphibious spherical robots. Micromachines, 11, 71.10.3390/mi11010071 ↗
29. He, Y. L., Zhu, L. Q., Sun, G. K., Qiao, J. F., & Guo, S. X. (2019). Underwater motion characteristics evaluation of multi amphibious spherical robots. Microsystem Technologies, 25, 499–508.10.1007/s00542-018-3986-z ↗
30. Fossen, T. I. (1999). Guidance and control of ocean vehicles. University of Trondheim.
31. Ma, Y. N., Gong, Y. J., Xiao, C. F., Gao, Y., & Zhang, J. (2018). Path planning for autonomous underwater vehicles: An ant colony algorithm incorporating alarm pheromone. IEEE Transactions on Vehicular Technology, 68, 141–154.10.1109/TVT.2018.2882130 ↗
32. Sahu, C., Parhi, D. R., & Kumar, P. B. (2018). An approach to optimize the path of humanoids using adaptive ant colony optimization. Journal of Bionic Engineering, 15, 623–635.10.1007/s42235-018-0051-7 ↗