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研究生:陳柄宏
研究生(外文):CHEN, BING-HONG
論文名稱:基於二型模糊神經控制器之阿克曼無人駕駛車輛導航控制
論文名稱(外文):Navigation Control of Ackerman Driverless Vehicle Using a Type-2 Fuzzy Neural Controller
指導教授:游正義林正堅林正堅引用關係
指導教授(外文):YU, CHENG-YILIN, CHENG-JIAN
口試委員:游正義林正堅郭世崇潘欣泰
口試委員(外文):YU, CHENG-YILIN , CHENG-JIANKUO, SHYE-CHORNGPAN, SHING-TAI
口試日期:2022-06-29
學位類別:碩士
校院名稱:國立勤益科技大學
系所名稱:資訊工程系
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2022
畢業學年度:110
語文別:中文
論文頁數:89
中文關鍵詞:阿克曼無人駕駛車輛模糊神經網路模糊控制粒子群優化
外文關鍵詞:Ackerman Driverless VehicleFuzzy neural networkParticle swarm optimizationFuzzy control 
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  • 下載下載:38
  • 收藏至我的研究室書目清單書目收藏:0
隨著自動導航的進步,導航控制也成為了車子移動的核心之一,為了能夠讓車子在未知的環境下完成運動控制和避障等功能,使用增強式學習周遭的環境,配合設計的適應函數來評估未知環境中的效能,適應值較好的為目標,來達到未知環境導航的目的,因此我們提出一個新的二型神經模糊控制器,和基於貝葉斯之動態分群粒子群演算法,把權重和因子根據當前適應值的好壞進行調整,找到最佳的參數配合二型神經模糊控制器實現導航功能,與其他的方法比較,本文的適應值皆從0.95提升到0.97,導航控制方面,也有著最短的時間和距離,實際的阿克曼無人自駕車沿牆實驗中,針對牆壁的距離的數據顯示,阿克曼無人自駕車有實現在沿牆走的移動上,並且能夠應用在真實的阿克曼無人駕駛車輛導航。
With the advancement of automatic navigation, navigation control has become one of the core of vehicle movement. In order to enable the vehicle to complete the functions of motion control and obstacle avoidance in an unknown environment, we use augmented learning to evaluate the performance in an unknown environment based on the surrounding environment with the designed adaptation function, and aim to achieve navigation in an unknown environment based on the better adaptation value. Therefore, we propose a new type II neural fuzzy controller, and based on Bayesian dynamic fractional swarm particle algorithm, we adjust the weights and factors according to the current adaptation value, and find the best parameters to achieve the navigation function with the type II neural fuzzy controller, and compare with other methods, the adaptation value of this paper is increased from 0.95 to 0.97, and the navigation control has the shortest time and distance, and the actual Ackermann unmanned self-driving vehicle. The data of the distance along the wall in the experiment shows that the Ackermann unmanned vehicle has achieved the movement along the wall and can be applied in the real Ackermann unmanned vehicle navigation.
摘要 I
Abstract III
誌謝 V
目錄 VI
圖目錄 IX
表目錄 XIII
第一章 緒論 1
1.1 研究動機 1
1.2 研究目的 3
1.3 論文架構 4
第二章 文獻探討 5
第三章 基於二型模糊神經控制器之阿克曼無人駕駛車輛導航控制 10
3.1 二型模糊神經控制器 12
3.2 基於貝葉斯動態分群之粒子群演算法(The Proposed Bayesian Development Group Particle Swarm Optimization,BDGPSO) 16
3.3 阿克曼轉向系統 28
3.4 沿牆移動行為學習 31
第四章 實驗結果 37
4.1 貝葉斯優化PSO參數結果 38
4.2 加權係數之實驗結果 40
4.3 利用T2FNC之實驗結果 44
4.2.1 T2FNC角速度輸出 44
4.2.2 T2FNC線速度輸出和角速度輸出 50
4.4 不同演算法於沿牆移動之效能 55
4.4.1 不同演算法於訓練環境中角速度與線速度之比較 55
4.4.2 不同演算法於測試環境1中角速度與線速度之比較 59
4.4.3 不同演算法於測試環境2中角速度與線速度之比較 62
4.5 阿克曼無人駕駛車輛導航控制 66
4.5.1 導航管理者(Navigation Manager) 66
4.5.2導航管理者於不同地形之實驗結果 68
第五章 自主研發的阿克曼無人駕駛車輛於實際環境中測試 75
5.1 實際環境 75
5.1.1 角速度於實際環境的移動情況 76
5.1.2 角速度與線速度於實際環境的移動情況 78
第六章 結論與未來工作 80
參考文獻 82
附錄 89
[1]O. Liu, S. Yuan and Z. Li, "A Survey on Sensor Technologies for Unmanned Ground Vehicles," 2020 3rd International Conference on Unmanned Systems (ICUS), 2020, pp. 638-645, doi: 10.1109/ICUS50048.2020.9274845.
[2]L. Wellhausen, A. Dosovitskiy, R. Ranftl, K. Walas, C. Cadena and M. Hutter, "Where Should I Walk? Predicting Terrain Properties From Images Via Self-Supervised Learning," in IEEE Robotics and Automation Letters, vol. 4, no. 2, pp. 1509-1516, April 2019, doi: 10.1109/LRA.2019.2895390.
[3]G. Kahn, P. Abbeel and S. Levine, "BADGR: An Autonomous Self-Supervised Learning-Based Navigation System," in IEEE Robotics and Automation Letters, vol. 6, no. 2, pp. 1312-1319, April 2021, doi: 10.1109/LRA.2021.3057023.
[4]R. S. Sutton, A. G. Barto, Reinforcement Learning: An Introduction, 1998, MIT Press.
[5]M. Faisal, M. Algabri, B. M. Abdelkader, H. Dhahri and M. M. Al Rahhal, "Human Expertise in Mobile Robot Navigation," in IEEE Access, vol. 6, pp. 1694-1705, 2018, doi: 10.1109/ACCESS.2017.2780082.
[6]S. Sahloul, D. Benhalima and C. Rekik, "Comparative study of hybrid fuzzy loMTGC methods for mobile robot navigation in unknown environments," 2019 19th International Conference on Sciences and Techniques of Automatic Control and Computer Engineering (STA), 2019, pp. 170-175, doi: 10.1109/STA.2019.8717260.
[7]Y. Saidi, M. Tadjine and A. Nemra, "Robust Waypoints navigation using Fuzzy Type 2 Controller," 2019 International Conference on Advanced Electrical Engineering (ICAEE), 2019, pp. 1-6, doi: 10.1109/ICAEE47123.2019.9015101.
[8]H. M. Yudha, T. Dewi, N. Hasana, P. Risma, Y. Oktarini and S. Kartini, "Performance Comparison of Fuzzy LoMTGC and Neural Network Design for Mobile Robot Navigation," 2019 International Conference on Electrical Engineering and Computer Science (ICECOS), 2019, pp. 79-84, doi: 10.1109/ICECOS47637.2019.8984577.
[9]J. Wang, Z. Ma and X. Chen, "Generalized Dynamic Fuzzy NN Model Based on Multiple Fading Factors SCKF and its Application in Integrated Navigation," in IEEE Sensors Journal, vol. 21, no. 3, pp. 3680-3693, 1 Feb.1, 2021, doi: 10.1109/JSEN.2020.3022934.
[10]J. Chen, F. Ye and T. Jiang, "Numerical analyses of three inertia-weight-improvement-based particle swarm optimization algorithms," 2017 2nd IEEE International Conference on Computational Intelligence and Applications (ICCIA), 2017, pp. 150-154, doi: 10.1109/CIAPP.2017.8167198.
[11]J. Liu, S. Anavatti and M. G. Hussein Abbass, "Comprehensive Learning Particle Swarm Optimisation with Limited Local Search for UAV Path Planning," 2019 IEEE Symposium Series on Computational Intelligence (SSCI), 2019, pp. 2287-2294, doi: 10.1109/SSCI44817.2019.9002992.
[12]Y. Ren and S. Liu, "Modified Particle Swarm Optimization Algorithm for Engineering Structural Optimization Problem," 2017 13th International Conference on Computational Intelligence and Security (CIS), 2017, pp. 504-507, doi: 10.1109/CIS.2017.00117.
[13]Y. Li, Y. Zhang, G. Zhou and Y. Gong, "Bayesian Optimization with Particle Swarm," 2021 International Joint Conference on Neural Networks (IJCNN), 2021, pp. 1-6, doi: 10.1109/IJCNN52387.2021.9533761.
[14]M. Schwaab, E. C. Biscaia, J. L. Monteiro and J. C. Pinto, "Nonlinear parameter estimation through particle swarm optimization", Chemical Engineering Science, vol. 63, no. 6, pp. 1542-1552, 2008.
[15]B. Shahriari, K. Swersky, Z. Wang, R. P. Adams and N. De Freitas, "Taking the human out of the loop: A review of bayesian optimization", Proceedings of the IEEE, vol. 104, no. 1, pp. 148-175, 2015.
[16]Z. Wenjing, "Parameter identification of lugre friction model in servo system based on improved particle swarm optimization algorithm", 2007 Chinese Control Conference, pp. 135-139, 2007.
[17]M. Schwaab, E. C. Biscaia, J. L. Monteiro and J. C. Pinto, "Nonlinear parameter estimation through particle swarm optimization", Chemical Engineering Science, vol. 63, no. 6, pp. 1542-1552, 2008.
[18]B. Son, J. -S. Kim, J. -W. Kim, Y. -J. Kim and S. -Y. Jung, "Adaptive Particle Swarm Optimization Based on Kernel Support Vector Machine for Optimal Design of Synchronous Reluctance Motor," in IEEE Transactions on Magnetics, vol. 55, no. 6, pp. 1-5, June 2019, Art no. 8202105, doi: 10.1109/TMAG.2019.2902935.
[19]M. Cheng and D. Prayogo, "Symbiotic Organisms Search: A New Metaheuristic Optimization Algorithm", Comput. Struct., vol. 139, pp. 98-112, 2014.
[20]K. Ahiska, M. K. Ozgoren and M. K. Leblebicioglu, "Energy and Time Optimal Autopilot for Electric Vehicles Performing Ackerman Cornering," in IEEE Transactions on Intelligent Transportation Systems, doi: 10.1109/TITS.2022.3159747.
[21]Z. M. U. Din, W. Razzaq, U. Arif, W. Ahmad and W. Muhammad, "Real Time Ackerman Steering Angle Control for Self-Driving Car Autonomous Navigation," 2019 4th International Conference on Emerging Trends in Engineering, Sciences and Technology (ICEEST), 2019, pp. 1-4, doi: 10.1109/ICEEST48626.2019.8981710.
[22]S. Talia, "A multimodal approach for localization of Ackerman steering micro ground vehicles in bad GPS reception environments," 2019 3rd International Conference on Recent Developments in Control, Automation & Power Engineering (RDCAPE), 2019, pp. 64-69, doi: 10.1109/RDCAPE47089.2019.8979000.
[23]H. Chi and Z. Zhu, "Research on Ackerman Driverless Vehicle Control Strategy Based on IMU Steering Calibration and Inverted Parabolic Speed Control," 2021 IEEE International Conference on Consumer Electronics and Computer Engineering (ICCECE), 2021, pp. 67-74, doi: 10.1109/ICCECE51280.2021.9342314.
[24]G. C. Lee, C. K. Loo and N. Masuyama, "Parameters Estimation in TopoloMTGCal Kernel Bayesian ART using Multi-objective Particle Swarm Optimization," 2018 IEEE Symposium Series on Computational Intelligence (SSCI), 2018, pp. 1595-1601, doi: 10.1109/SSCI.2018.8628623.
[25]F. Shen et al., "Bayesian-based Resonance Ultrasound Spectroscopy with Particle Swarm Optimization," 2021 IEEE International Ultrasonics Symposium (IUS), 2021, pp. 1-3, doi: 10.1109/IUS52206.2021.9593410.
[26]S. Sivaraman, Learning Modeling and Understanding Vehicle Surround Using Multi-Modal Sensing, 2013.
[27]J. Lin, Y. Tan and J. Tian, "Inter-frame Correlation Based on Moving Vehicle Target Detection in Infrared Image Sequences," 2017 International Conference on Computer Technology, Electronics and Communication (ICCTEC), 2017, pp. 1187-1191, doi: 10.1109/ICCTEC.2017.00258.
[28]A. S. Olagoke, H. Ibrahim and S. S. Teoh, "Literature Survey on Multi-Camera System and Its Application," in IEEE Access, vol. 8, pp. 172892-172922, 2020, doi: 10.1109/ACCESS.2020.3024568.
[29]Y. Li et al., "Deep Learning for LiDAR Point Clouds in Autonomous Driving: A Review," in IEEE Transactions on Neural Networks and Learning Systems, vol. 32, no. 8, pp. 3412-3432, Aug. 2021, doi: 10.1109/TNNLS.2020.3015992.
[30]C. -J. Kim and D. Chwa, "Obstacle Avoidance Method for Wheeled Mobile Robots Using Interval Type-2 Fuzzy Neural Network," in IEEE Transactions on Fuzzy Systems, vol. 23, no. 3, pp. 677-687, June 2015, doi: 10.1109/TFUZZ.2014.2321771.
[31]C. -J. Lin, H. -Y. Lin and C. -Y. Yu, "Using a Type-2 Neural Fuzzy Controller for Navigation Control of Evolutionary Robots," 2018 International Symposium on Computer, Consumer and Control (IS3C), 2018, pp. 306-309, doi: 10.1109/IS3C.2018.00084.
[32]X. Zhang, X. Zhang, S. Ho and W. Fu, "A Modification of Artificial Bee Colony Algorithm Applied to Loudspeaker Design Problem", Magnetics IEEE Transactions on, vol. 50, no. 2, pp. 737-740, 2014.
[33]Y. L. Li, Z. H. Zhan, Y. J. Gong, W. N. Chen, J. Zhang and Y. Li, "Differential Evolution with an Evolution Path: A DEEP Evolutionary Algorithm", IEEE Trans. on Cybernetics, 2014.
[34]S. L. Ho, S. Yang, G. Ni and J. Huang, "A Quantum-Based Particle Swarm Optimization Algorithm Applied to Inverse Problems", IEEE Trans. Magn., vol. 49, no. 5, pp. 2069-2072, May. 2013.
[35]J. Yin and W. Fu, "A Hybrid Path Planning Algorithm Based on Simulated Annealing Particle Swarm for The Self-driving Car," 2018 International Computers, Signals and Systems Conference (ICOMSSC), 2018, pp. 696-700, doi: 10.1109/ICOMSSC45026.2018.8941726.
[36]J. Song and W. Yi, "Improvement of original particle swarm optimization algorithm based on simulated annealing algorithm," 2012 8th International Conference on Natural Computation, 2012, pp. 777-781, doi: 10.1109/ICNC.2012.6234724.
[37]S. Jun and L. Jian, "An Improved Self-Adaptive Particle Swarm Optimization Algorithm with Simulated Annealing," 2009 Third International Symposium on Intelligent Information Technology Application, 2009, pp. 396-399, doi: 10.1109/IITA.2009.476.
[38]P. Sharma and P. Bajaj, "Performance Analysis of Vehicle Classification System Using Type-1 Fuzzy, Adaptive Neural-Fuzzy and Type-2 Fuzzy Inference System," 2009 Second International Conference on Emerging Trends in Engineering & Technology, 2009, pp. 581-584, doi: 10.1109/ICETET.2009.171.
[39]Y. Lin, J. Chang, N. R. Pal and C. Lin, "A Mutually Recurrent Interval Type-2 Neural Fuzzy System (MRIT2NFS) With Self-Evolving Structure and Parameters," in IEEE Transactions on Fuzzy Systems, vol. 21, no. 3, pp. 492-509, June 2013, doi: 10.1109/TFUZZ.2013.2255613.
[40]N. Baklouti and A. M. Alimi, "Interval type-2 beta fuzzy neural network for wheeled mobile robots obstacles avoidance," 2017 International Conference on Advanced Systems and Electric Technologies (IC_ASET), 2017, pp. 481-486, doi: 10.1109/ASET.2017.7983740.

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