NOVEL TOPOLOGICAL RELATIONSHIP SOLUTIONS TO THE ALV MULTI-INDEGREE–MULTI-OUTDEGREE TASK SEQUENCE PLANNING PROBLEM

Yandong Liu,∗,∗∗ Dong Han,∗,∗∗ Lujia Wang,∗ and Cheng-zhong Xu∗∗∗

References

  1. [1] H. Liang, T. Mei, R. Huang, J. Chen, P. Zhao, and C. Sun, A new dynamic obstacle collision avoidance system for autonomous vehicles, International Journal of Robotics and Automation, 30, 2015, 278–288.
  2. [2] W. Smuda, P.L. Muench, G.R. Gerhart, and K.L. Moore, Autonomy and manual operation in a small robotic system for under-vehicle inspections at security checkpoints, Unmanned Ground Vehicle Technology IV, Orlando, FL, 2002, 1–12.
  3. [3] J.B. Mcmillion, Autonomous cleaning system, Google Patents, 2017.
  4. [4] T.A.S. Nielsen and S. Haustein, On sceptics and enthusiasts: What are the expectations towards self-driving cars? Transport Policy, 66, 2018, 49–55.
  5. [5] Y. Liu, L. Wang, H. Huang, M. Liu, and C.-Z. Xu, A novel swarm robot simulation platform for warehousing logistics, 2017 IEEE Int. Conf. on Robotics and Biomimetics (ROBIO), Parisian Macao, China, 2017, 2669–2674.
  6. [6] O. Sporns, Graph theory methods for the analysis of neural connectivity patterns, Neuroscience databases (Berlin: Springer, 2003), 171–185.
  7. [7] C. Lin, H. Wang, J. Yuan, and M. Fu, An online path planning method based on hybrid quantum ant colony optimization for AUV, International Journal of Robotics & Automation, 33, 2018, 435–444.
  8. [8] I.A. Chaudhry and A.A. Khan, A research survey: review of flexible job shop scheduling techniques, International Transactions in Operational Research, 23, 2016, 551–591.
  9. [9] C. Pang, J. Wang, Y. Cheng, H. Zhang, and T. Li, Topological sorts on DAGs, Information Processing Letters, 115, 2015, 298–301.
  10. [10] T. Vodopivec and B. Ster, Selective topological approach to mobile robot navigation with recurrent neural networks, International Journal of Robotics and Automation, 30, 2015, 182–200.
  11. [11] L. Zhang, H. Lv, D. Tan, et al., Adaptive quantum genetic algorithm for task sequence planning of complex assembly systems, Electronics Letters, 54, 2018, 870–872.
  12. [12] X. Wu, J. Liu, C. Huang, M. Su, and T. Xu, 3-D path following of helical microswimmers with an adaptive orientation compensation model, IEEE Transactions on Automation Science and Engineering, 17, 2019, 17, 823–832.
  13. [13] N. Wantia, M. Esen, A. Hengstebeck, et al., Task planning for human robot interactive processes, 2016 IEEE 21st Int. Conf. on Emerging Technologies and Factory Automation (ETFA), Berlin, Germany, 2016, 1–8.
  14. [14] P. Toth and D. Vigo, The vehicle routing problem (Philadelphia: SIAM, 2002).
  15. [15] T. Cao and A.C. Sanderson, Task sequence planning using fuzzy Petri nets, IEEE Transactions on Systems, Man, and Cybernetics, 25, 1995, 755–768.
  16. [16] C. Jung, H.-J. Kim, and T.-E. Lee, A branch and bound algorithm for cyclic scheduling of timed Petri nets, IEEE Transactions on Automation Science and Engineering, 12, 2013, 309–323.
  17. [17] J. Li, B. Xu, Y. Yang, and H. Wu, Three-phase qubits-based quantum ant colony optimization algorithm for path planning of automated guided vehicles, International Journal of Robotics and Automation, 34, 2019, 156–163.
  18. [18] D.-Y. Lin and S.-L. Hwang, Use of neural networks to achieve dynamic task allocation: a flexible manufacturing system example, International Journal of Industrial Ergonomics, 24, 1999, 281–298.
  19. [19] R. Roberti and P. Toth, Models and algorithms for the asymmetric traveling salesman problem: an experimental comparison, EURO Journal on Transportation and Logistics, 1, 2012, 113–133.
  20. [20] M.R. Garey and D.S. Johnson, Computers and intractability (San Francisco, Freeman, 1979).

Important Links:

Go Back