References
- Berglund, T., Brodnik, A., Jonsson, H., Staffanson, M., & Soderkvist, I. (2010). Planning smooth and obstacle-avoiding B-spline paths for autonomous mining vehicles. IEEE Transactions on Automation Science and Engineering, 7(1), 167–172. https://doi.org/https://doi.org/10.1109/TASE.2009.2015886
- Dorigo, M., Birattari, M., & Thomas, S. (2006). Ant colony optimization. IEEE Computational Intelligence Magazine, 1(4), 28–39. https://doi.org/https://doi.org/10.1109/CI-M.2006.248054
- Gao, W., Tang, Q., Ye, B., Yang, Y., & Yao, J. (2020). An enhanced heuristic ant colony optimization for mobile robot path planning. Soft Computing, 24, 6139–6150. https://doi.org/https://doi.org/10.1007/s00500-020-04749-3
- Ge, S. (2019). Present situation and development direction of coal mine robots. China Coal, 45(7), 18–27. https://doi.org/https://doi.org/10.19880/j.cnki.ccm.2019.07.004
- Lee, J. (2017). Heterogeneous-ants-based path planner for global path planning of mobile robot applications. International Journal of Control, Automation and Systems, 15(4), 1754–1769. https://doi.org/https://doi.org/10.1007/s12555-016-0443-6
- Lu, W., Fu, H., & Zhao, R. (2019). Research on topographic perception system and path planning method of underground detection and search and rescue robot in coal mine. Chinese Journal of Sensors and Actuators, 32(7), 979–985.
- Luo, Q., Wang, H., Zheng, Y., & He, J. (2020). Research on path planning of mobile robot based on improved ant colony algorithm. Neural Computing and Applications, 32, 1555–1566. https://doi.org/https://doi.org/10.1007/s00521-019-04172-2
- Ma, X., & Mao, R. (2018). Path planning for coal mine robot to avoid obstacle in gas distribution area. International Journal of Advanced Robotic Systems, 15(1). https://doi.org/https://doi.org/10.1177/1729881417751505
- Tan, Y., Yang, W., & Xu, Z. (2017). Three-dimensional path planning method for robot in underground local complex space. Journal of China Coal Society, 42(6), 1634–1642. https://doi.org/https://doi.org/10.13225/j.cnki.jccs.2016.1047
- Tao, J., Jiang, Y., Liu, Y., Xin, Y., & Luo, J. (2019). Research on path smoothing algorithm of coal mine rescue robot. Industry and Mine Automation, 45(10), 49–54. https://doi.org/https://doi.org/10.13272/j.issn.1671-251x.2019050069
- Xu, S. (2014). Global path planning for coal mine rescure robot based on artificial bee colony algorithm. Coal Technology, 33(1). https://doi.org/https://doi.org/10.13301/j.cnki.ct.2014.01.092
- Xu, J., & Huang, Y. (2019). Path planning of robot in coal mine using genetic membrane algorithms. In Proceedings of the 2nd International Conference on Information Technologies and Electrical Engineering (pp. 1–5).
- Yang, H., Qi, J., Miao, Y., Sun, H., & Li, J. (2019). A new robot navigation algorithm based on a double-layer ant algorithm and trajectory optimization. IEEE Transactions on Industrial Electronics, 66(11), 8557–8566. https://doi.org/https://doi.org/10.1109/TIE.41
- Yang, X., Wang, S., Wang, H., Chen, Y., & Lv, Y. (2019). Application of GNSS/SINS integrated navigation system based on EKF. Journal of Shandong University of Science and Technology (Natural Science), 38(6), 114–122. https://doi.org/https://doi.org/10.16452/j.cnki.sdkjzk.2019.06.015
- Yao, Z., Ren, Z., & Chen, Y. (2014). Path planning for mine rescue robot based on AFSA. Coal Mine Machinery, 35(4), 59–61. https://doi.org/https://doi.org/10.13436/j.mkjx.201404026
- Yin, Z., Lv, Y., & Lv, J. (2020). An optimized SLAM substation complex environment map construction. Journal of Shandong University of Science and Technology (Natural Science), 39(2), 126–132. https://doi.org/https://doi.org/10.16452/j.cnki.sdkjzk.2020.02.015
- Zeng, N., Song, D., Li, H., You, Y., Liu, Y., & Alsaadi, F. E. (2021). A competitive mechanism integrated multi-objective whale optimization algorithm with differential evolution. Neurocomputing, 432, 170–182. https://doi.org/https://doi.org/10.1016/j.neucom.2020.12.065
- Zeng, N., Wang, Z., Liu, W., Zhang, H., Hone, K., & Liu, X. (2020). A dynamic neighborhood-based switching particle swarm optimization algorithm. IEEE Transactions on Cybernetics. https://doi.org/https://doi.org/10.1109/TCYB.2020.3029748
- Zeng, N., Wang, Z., Zhang, H., Kim, K.-E., Li, Y., & Liu, X. (2019). An improved particle filter with a novel hybrid proposal distribution for quantitative analysis of gold immunochromatographic strips. IEEE Transactions on Nanotechnology, 18, 819–829. https://doi.org/https://doi.org/10.1109/TNANO.7729
- Zeng, N., Zhang, H., Chen, Y., Chen, B., & Liu, Y. (2016). Path planning for intelligent robot based on switching local evolutionary PSO algorithm. Assembly Automation, 36(2), 120–126. https://doi.org/https://doi.org/10.1108/AA-10-2015-079
- Zhao, J., Zhu, L., Liu, G., Liu, G., & Han, Z. (2009). A modified genetic algorithm for global path planning of searching robot in mine disasters. In Proceedings of the 2009 IEEE International Conference on Mechatronics and Automation (pp. 4936–4940).