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Review

A cooperative strategy of multi-arm coal gangue sorting robot based on immune dynamic workspace

ORCID Icon, , , , , & show all
Pages 794-814 | Received 16 Aug 2021, Accepted 13 May 2022, Published online: 17 May 2022

References

  • Atay, N., and B. Bayazit. 2006. Mixed-integer linear programming solution to multi-robot task allocation problem. Washington Univ:15–26.
  • Botelho, S., and R. Alami. 1999. M+: a scheme for multi-robot cooperation through negotiated task allocation and achievement. Proceedings of IEEE International Conference on Robotics and Automation, Detroit, MI, USA,1234–39. doi:10.1109/ROBOT.1999.772530.
  • Chaimo Wicz, L., F. M. C. Mario, and V. Kumar. 2002. Dynamic role assignment for cooperative robots. Proceedings of IEEE International Conference on Robotics and Automation, Washington, DC, USA, 293–98. doi:10.1109/ROBOT.2002.1013376.
  • Choi, I. S., and J. S. Choi. 2012. Leader-follower formation control using PID controller. International Conference on Intelligent Robotics and Applications, Montreal, QC, Canada, 7050:625–34. doi:10.1007/978-3-642-33515-0_61.
  • Di Lillo, P., F. Pierri, G. Antonelli, F. Caccavale, A. Ollero. 2021. A framework for set-based kinematic control of multi-robot systems. Control Engineering Practice 106 (1):104669. doi:10.1016/j.conengprac.2020.104669.
  • Dias, M. B. T. 2004. raderBots: A new paradigm for robust and efficient multirobot coordination in dynamic environments.Pittsburgh. Carnegie Mellon University: Robot-Ics Institute,Carnegie Mellon University.
  • Fan, H., R. Xiangdong, and W. Tong. 2015. Improved genetic algorithm for task assignment of power network attack UAV squadron. Fire Control & Command Control 40 (4):51–54. doi:10.3969/j.1002-0640.2015.04.013.
  • Fang, Tang, and L. E Parker. 2005. ASyMTRe: Automated synthesis of multi-robot task solution through software reconfiguration. Proceedings of IEEE International Conference on Robotics and Automation.[S.l.], Barcelona, Spain,1501–08. doi:10.1109/ROBOT.2005.1570327.
  • Farinelli, A., L. Iocchi, and D. Nardi. 2017. Distributed on-line dynamic task ssignment for multi-robot patrolling. Autonomous Robots 41:1321–45. doi:10.1007/s10514-016-9579-8.
  • Feng, L., S. Wang, R. Zhang, Z. Chai, J. Long, and M. Zeng. 2022. Study on key factors affecting separation performance of aerated fluidized bed. International Journal of Coal Preparation and Utilization 42 (2):171–90. doi:10.1080/19392699.2019.1590343.
  • Gao, Y. Y., and W. Wei. 2006. Multi-robot autonomous cooperation integrated with immune based dynamic task allocation. Proceedings of the 6th International Conference on Intelligent Systems Design and Applications, Jian, China, 586–91. doi:10.1109/ISDA.2006.253902.
  • Gerkey, B. P., and M. J. Mataric. 2002. Sold!: auction methods for multirobot coordination. IEEE Transactions on Robotics and Automation 18 (5):758–86. doi:10.1109/TRA.2002.803462.
  • Huck, T., L. Hornung, and C. Ledermann. 2021. Risk assessment tools for industrial human-robot collaboration: Novel approaches and practical needs. Safety Science 141 (13):105288. doi:10.1016/j.ssci.2021.105288.
  • Ku, Y.-D., J.-H. Yang, H.-Y. Fang. 2020. Optimization of grasping efficiency of a robot used for sorting construction and demolition waste. International Journal of Automation and Computing 17 (5):691–700. doi:10.1007/s11633-020-1237-0.
  • Li, S., X. Xu, and Zuo L. 2015. Task allocation of multi-robot systems based on improved genetic algorithms. IEEE International Conference on Mechatronics and Automation, Beijing, China. IEEE:1430–35. doi:10.1109/ICMA.2015.7237695.
  • Li, J. 2019. Optimal design of transportation distance in logistics supply chain model based on data mining algorithm[J]. Cluster Computing 22 (1):115–18. doi:10.1007/s10586-018-2544-x.
  • Moslehi, M. S., H. Sahebi, and A. Teymouri. 2020. A multi-objective stochastic model for a reverse logistics supply chain design with environmental considerations[J]. Journal of Ambient Intelligence and Humanized Computing 27 (2):6–13. doi:10.1007/s12652-020-02538-2.
  • Muxi, J., L. Rui, L. Qisheng. 2021. High speed long-term visual object tracking algorithm for real robot systems. Neurocomputing 434:268–84. doi:10.1016/j.neucom.2020.12.113.
  • Nikou, A., S. Heshmati-alamdari, and V. Dimos. 2020. Dimarogonas scalable time-constrained planning of multi-robot systems. Autonomous Robots 44:1451–67. doi:10.1007/s10514-020-09937-6.
  • Pellegrinelli, S. 2019. Configuration and reconfiguration of robotic systems for waste macro sorting. The International Journal of Advanced Manufacturing Technology 102:3677–87. doi:10.1007/s00170-019-03289-x.
  • Peng, W. A. N. G., C. A. O. Xiangang, X. I. A. Jing. 2019. Research on multi manipulator coal and gangue sorting robot system based on machine vision. Industry and Mine Automation 45 (9):47–53. doi:10.13272/j.1671-251x.17442.
  • Peng, W. A. N. G., C. A. O. Xiangang, M. A. Hongwei. 2020. Dynamic target steady and accurate grasping algorithm of gangue sorting robot based on cosine theorem-PID. Joumal of China Coalsociety 45(12):4240–47. Publisher: China Coal Society. doi:10.13225/j.cnki.jccs.2019.1565.
  • Richards, C., and N. Papanikolopoulos. 1997. Detection and tracking for robotic visual servoing system. Robotics and Computer-Integrated Manufacturing 13 (2):101–20. doi:10.1016/S0736-5845(96)00034-8.
  • Sariel, S., and T. Balch. 2006. A distributed multi-robot cooperation framework for real time task achievement (pp. 187–96). Tokyo: Springer. doi:10.1007/4-431-35881-1_19.
  • Shaferman, V., and T. Shima. 2013. Tracking multiple ground targets in urban environments using cooperating unmanned aerial vehicles. Journal of Dynamic Systems, Measurement, and Control 137 (5): 051010(11 pages). doi:10.1115/1.4028594.
  • Werger, B., and M. J. Mataric. 2000. M.J.: Broadcast of local eligibility: Behavior based control for strongly cooperative multi-robot teams. Proceedings of Autonomous Agents. Barcelona, Spain 12( 781):21–22. doi:10.1145/336595.336621.
  • Zhu, H., M. C. Zhou, and R. Alkins. 2012. Group role assignment via a Kuhn-Munkres algorithm-based solution. IEEE Transactions on Systems,Man and Cybemetics, Part A:Systems and Humans 42 (3):739–50. doi:10.1109/TSMCA.2011.2170414.
  • Zlot, R., A. Stentz, M. B. Dias. 2002. Multi-robot exploration controlled by a market econmy. International Conference on Intelligent Robotics and Applications, Washington, DC, USA, 3016–23. doi:10.1109/ROBOT.2002.1013690.

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