(3.238.99.243) 您好!臺灣時間:2021/05/15 18:18
字體大小: 字級放大   字級縮小   預設字形  
回查詢結果

詳目顯示:::

: 
twitterline
研究生:楊惠文
研究生(外文):YANG,HUI-WEN
論文名稱:應用腦波於循跡避障機器人系統之研究
論文名稱(外文):Apply Brainwaves to Robot System with Automatic Traking and Obstacle Avoidance
指導教授:孫光天孫光天引用關係
指導教授(外文):SUN,KOUN-TEM
口試委員:李建億詹信德
口試委員(外文):LEE,CHIEN-ICHAN,HSIN-TE
口試日期:2016-06-24
學位類別:碩士
校院名稱:國立臺南大學
系所名稱:數位學習科技學系碩博士班
學門:教育學門
學類:教育科技學類
論文種類:學術論文
論文出版年:2016
畢業學年度:104
語文別:中文
論文頁數:66
中文關鍵詞:事件相關電位N2P3腦波控制機器人循跡避障
外文關鍵詞:Event-related potentialsN2P3brainwave controlautomatic trackingobstacle avoidance
相關次數:
  • 被引用被引用:0
  • 點閱點閱:169
  • 評分評分:
  • 下載下載:23
  • 收藏至我的研究室書目清單書目收藏:1
腦波控制系統在事件相關電位(ERPs)N200和P300上有相當不錯的成就,本研究即以事件相關電位的N2P3成分作為腦波特徵提取的依據,開發一套腦波控制與機器人自動循跡及避障之系統。在機器人自動循跡與避障的部份,以PID控制理論和決策樹避障演算法實現自動循跡、避障之功能;於腦波控制系統的部份,以10-20制之電極點O1(大腦視覺區)作為腦波資料蒐集的電極點位置,分析O1 的ERPs中N200、P300和N2P3成分,在目標與非目標差異之顯著性和振幅,發現N2P3之顯著性和振幅皆比N200或P300更有利於判斷使用者的意圖。本研究之腦波控制系統使用特殊編碼刺激代替傳統的行列刺激,創造更加快速的腦波控制能力,經20人測試本研究開發之系統,發現系統平均正確率為83.4%,證實腦波控制與機器人自我控制系統結合之價值,提供重度肢體障礙者與機器人分工合作來達成任務之可行性研究。
Recent studies have shown good results in brainwave control system based on the N200 potentials and the P300 potentials of event-related potentials (ERPs). In this study, the N2P3 component of event-related potentials is used to develop a brainwave-controlled automatic tracking and the obstacle avoidance robot system. In the robot system, this study used PID control theory and decision-tree obstacle avoidance algorithm for automatic tracking and obstacle avoidance function. In the brainwave control system, we choose the electrode point O1 of 10-20 system to collect EEG data. The experimental results show the significant differences between target andnon-target, among N200, P300 and N2P3 of the event-related potentials. The results prove that the significant differences of N2P3 is higher than that of the N200 or P300. This new component of ERPs used in our research, and then generated a faster brainwave control system. Twenty subjects voluntarily attend the experiment. The system’s averaged correct rate is 83.4% which confirms the value of brainwave control system for providing severe physical disabilities as a assistive devices. The cooperative approaches between robot and brainwave control is feasible and verified in the research.
中文摘要 i
英文摘要 ii
目次 iii
表次 v
圖次 vi
第一章 緒論 1
第一節 研究動機 1
第二節 研究目的 2
第二章 文獻探討 3
第一節 大腦結構概述 3
第二節 腦機介面 6
第三節 事件相關電位 7
一、N200 8
二、P300 8
第四節 腦波技術應用 10
第五節 循跡系統 11
第六節 避障系統 12
第三章 研究設計 17
第一節 開發環境與設備 17
一、腦波設備 17
二、樂高機器人 18
三、中文發聲系統 20
第二節 系統設計 21
一、機器人循跡系統 21
二、機器人避障系統 23
三、機器人脫離與回歸循跡軌道機制 27
四、腦波控制介面 30
五、腦波控制系統 35
第三節 實驗設計 43
一、實驗對象與環境 43
二、實驗流程與資料蒐集 44
第四章 實驗結果 45
第一節 事件相關電位不同成分之檢定 45
第二節 不同介面之目標顯著性考驗 48
第三節 受測者資料統計分析 51
第五章 結論與未來展望 56
第一節 討論與結論 56
第二節 未來展望 58
參考文獻 59


一、中文部分
王宗一,林宗德(民94)。居家清潔機器人之全域覆蓋路徑規劃與實現。國立成功大學工程科學研究所碩士論文。
李玄景(民99)。中文語音認知處理之事件相關電位研究。國立臺南大學數位學習科技學系碩士班。
李顯宏,余志成(民92)。適形越障探測車之行動規劃與機電整合。第二十屆機械工程研討會論文集,台北:國立台灣大學。
徐金霆(民98)。閱讀理解英語短文對腦波變化率影響之案例研究。國立臺東大學教育學系所碩士論文。
陳美勇、鍾秉剛(民104)。工業4.0計畫中智慧型機器人發展之趨勢。中等教育,66:3,6-13。
黃冠豪(民96)。失眠認知行為治療前後生理指標的改變與療效的關係。國立政治大學心理學研究所碩士論文。
葉隆吉,顏紹鈞(民100)。具定位與路徑規劃功能之群組清掃機器人開發。私立大同大學機械工程研究所碩士論文。 
二、西文部分
Al-Haddad, A. A., Sudirman, R., Omar, C., Tumari, M., and Zubaidah, S. (2012, Feb.). Wheelchair Motion Control Guide Using Eye Gaze and Blinks Based on PointBug Algorithm. 2012 3rd International Conference on Intelligent Systems, Modelling and Simulation, 37–42.
Bell, C. J., Shenoy, P., Chalodhorn, R., and Rao, R. P. N. (2008). Control of a humanoid robot by a noninvasive brain-computer interface in humans, Journal of Neural Engineering, 5(2), 214–220.
Belluomo, P., Bucolo, M., Fortuna, L., and Frasca, M. (2012). Robot Control through Brain-Computer Interface for Pattern Generation, Complex Systems, 20(3), 243–251.
Bhattacharyya, S., Konar, A., and Tibarewala, D. N. (2014). Motor imagery, P300 and error-related EEG-based robot arm movement control for rehabilitation purpose. Medical & Biological Engineering & Computing, 52(12), 1007-1017.
Bonino, D., Ricciardi, E., Bernardi, G., Sani, L., Gentili, C., Vecchi, T., and Pietrini, P. (2015). Spatial imagery relies on a sensory independent, though sensory sensitive, functional organization within the parietal cortex: a fMRI study of angle discrimination in sighted and congenitally blind individuals. Neuropsychologia, 68, 59–70.
Borenstein, J., and Koren, Y. (1988). Obstacle avoidance with ultrasonic sensors. IEEE Journal of Robotics and Automation, 4(2), 213-218.
Brodmann, K. (1909). Vergleichende Lokalisationslehre der Grosshirnrinde. German: Leipzig : Johann Ambrosius Barth.
Brown, M., Funke, J., Erlien, S., Gerdes, J. C. (2016, 4 May). Safe driving envelopes for path tracking in autonomous vehicles. Control Engineering Practice, Retrieved from May 30, 2016, from http://www.sciencedirect.com/science/article/pii/S0967066116300831
Carlson, T., and Millán J. d. R. (2013). Brain-controlled wheelchairs: A robotic architecture, IEEE Robotics and Automation Magazine, 20(1), 65–73.
Catani, M., Dell'acqua, F., Vergani, F., Malik, F., Hodge, H., Roy, P., Valabregue, R., and Thiebaut de Schotten, M. (2012). Short frontal lobe connections of the human brain. Cortex, 48(2), 273–291.
Chou, H. C., Prataksita, Narendra., Lin, Y. T. and Kuo, C. H. (2016). P300 and Motor Imagery Based Brain-Computer Interface for Controlling Wheelchairs. Journal of Medical Devices, 8(3), 030906.
Donchin E., Spencer, K. M., and Wijesinghe, R. (2000). The mental prosthesis: assessing the speed of a P300-based brain–computer interface. IEEE Transactions on Rehabilitation Engineering, 8, 174–179.
Donchin, E., Spencer, K. M., and Wijesinghe, R. (2000). The Mental Prosthesis: Assessing the Speed of a P300-Based Brain–Computer Interface. IEEE Transactions On Rehabilitation Engineering, 8(2), 174-179.
Economo, C., and Koskinas, and G. N. (1925). Die Cytoarchitektonik der Hirnrinde des erwachsenen Menschen. German: Wien & Berlin: Springer.
Farwell, L. A., and Donchin, E. (1988). Talking off the top of your head: toward a mental prothesis utilizing event-related brain potentials. Electroencephalography clinical Neurophysiology, 70, 510–523.
Farwell, L. A., and Smith, S. S. (2001). Using Brain MERMER Testing to Detect Knowledge Despite Efforts to Conceal. Journal of Forensic Science, 46(1), 135-143.
Ferber, S., Humphrey, G. K., and Vilis, T. (2003). The lateral occipital complex subserves the perceptual persistence of motion-defined groupings. Cereb Cortex, 13(7), 716–721.
Folstein, J. R., and Van Petten, C. (2008). Influence of cognitive control and mismatch on the N2 component of the ERP: A review. Psychophysiology, 45(1), 152-170.
Gandhi, V., Prasad, G., Coyle, D., Behera, L., McGinnity, T. M. (2014). EEG-Based Mobile Robot Control Through an Adaptive Brain–Robot Interface. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 44(9), 1278-1285.
Gao, X., Xu, D., Cheng, M., and Gao, S. (2003). A BCI-based enviromental controller for the motion-disabled. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 11(2), 137-140.
Gautam, L., Verma, R. K., and Sharma, C. (2013). Developing Manual Control for a Line Follower Robot. Advance in Electronic and Electric Engineering, 3(3), 305-310.
Guger, C., Harkam, W., Hertnaes, C., and Pfurtscheller, G. (1999). Prosthetic control by an EEG-based brain-computer interface (BCI), Proc. AAATE', 99, 590–595.
Guruprasad, K. R. (2012). Egress Bug: a real time path planning algorithm for a mobile robot in an unknown environment. Advanced Computing, Networking and Security, 7135. 228-236, New York: Springer Berlin Heidelberg.
Hasan, I. H., Ramli, A. R., Ahmad, S. A., and Osman, R. (2013). P300-Based EEG Signal Interpretation System for Robot Navigation Control. World Applied Sciences Journal, 26(5), 566–572.
Heinrich, S. P. (2007).A primer on motion visual evoked potentials. Documenta Ophthalmologica. 114(2), 83–105. doi:10.1007/s10633-006-9043-8
Hochberg, L. R., Serruya, M. D., Friehs, G. M., Mukand J. A., Saleh, M., Caplan, A. H., Branner, A., Chen, D., Penn, R. D., and. Donoghue, J. P. (2006). Neuronal ensemble control of prosthetic devices by a human with tetraplegia, Nature, 442, 164–171.
Hong, B., Guo, F., Liu, T., Gao, X., and. Gao, S. (2009).N200-speller using motion-onset visual response” , Clinical Neurophysiology, 120(9), 1658-1666.
Islam, M. S., and. Rahman, M. A. (2013). Design and Fabrication of Line Follower Robot. Asian Journal of Applied Science and Engineering, 2(2), 27-32.
Kaplan, A. Y., Shishkin, S. L., Ganin, I. P., Basyul, I. A. and Zhigalov, A. Y. (2013). Adapting the P300-based brain–computer interface for gaming: a review, IEEE Transactions on Computational Intelligence and AI in Games, 5(2), 141–149.
Kaufmann, T., Herweg, A., and Kübler, A. (2014). Toward brain-computer interface based wheelchair control utilizing tactually-evoked event-related potentials. Journal of NeuroEngineering and Rehabilitation, 11(7).
Kazem, B. I., Hamad, A. H., and Mozael, M. M. (2010). Modified vector field histogram with a neural network learning model for mobile robot path planning and obstacle avoidance. International Journal of Advancements in Computing Technology, 2(5), 166-173.
Khare, V., Santhosh, J., Anand, S., and Bhatia, M. (2011). Brain Computer Interface Based Real Time Control of Wheelchair Using Electroencephalogram, International Journal of Soft Computing and Engineering, 1(5), 41–45.
Krusienski, D.J., Sellers, E.W., McFarland, D.J., Vaughan, T.M., and Wolpaw, J.R., (2008). Toward enhanced P300 speller performance. Journal of Neuroscience Methods, 167(1), 15-21.
Lech, R. K., and Suchan, B. (2013). The medial temporal lobe: Memory and beyond. Behavioural Brain Research, 254, pp. 45–49.
Li, M., Li,W., Niu, L. W, ; Zhou, H. H., Chen, G. S., and Duan, F. (2016). An Event-Related Potential-based Adaptive Model for Telepresence Control of Humanoid Robot Motion in an Environment with Cluster Obstacles. IEEE Transactions on Industrial Electronics, PP(99), 1-10.
Li, W., Jaramillo, C., and Li, Y. Y. (2011). A Brain Computer Interface Based Humanoid Robot Control System, In: IASTED International Conference on Robotics, Pittsburgh, . 390–396. (2011).
Lobo-Prat, J., Kooren, P. N., Stienen, A. H. A., Herder, J. L., Koopman, B. F. J. M., and Veltink, P. H. (2014).Non-invasive control interfaces for intention detection in active movement-assistive devices. Journal of Neuroengineering and Rehabilitation, 11(168).
Ma,J. X., Zhang, Y., Cichocki, A., Matsuno, F. (2014). A Novel EOG/EEG Hybrid Human–Machine Interface Adopting Eye Movements and ERPs: Application to Robot Control. IEEE Transactions on Biomedical Engineering, 62(3), 876-889.
McCane, L. M., Heckman, S. M., McFarland, D. J., Townsend, G., Mak, J. N., Sellers, E. W., Zeitlin, D., Tenteromano, L. M., Wolpaw, J.R., Vaughan, T. M.(2015).P300-based brain-computer interface (BCI) event-related potentials (ERPs): People with amyotrophic lateral sclerosis (ALS) vs. age-matched controls. Clin Neurophysiol, 126(11), 2124-2131.
Meneguello, J., Leonhardt, F.D., Pereira, L.D. (2006).Auditory processing in patients with temporal lobe epilepsy. Brazilian Journal Of Otorhinolaryngology, 72(4), 496–504.
Müller-Putz, G. R., and Pfurtscheller, G. (2008). Control of an electrical prosthesis with an SSVEP-based BCI, IEEE Transactions on Biomedical Engineering, 55(1), 361-364.
Renterghem, D. V., Wyns, B., and Devlaminck, D. (2011). Shared control between P300 BCI and robotic arm. International Journal of Bioelectromagnetism, 13(1), 2-4.
Ribas, G. C. (2010). The cerebral sulci and gyri. Neurosurg Focus. 28(2), E2.
Rondeau, L., Ruelas, R., Levrat, L., and Lamotte, M. (1997). A defuzzification method respecting the fuzzification, Fuzzy Sets and Systems, 86(3), 311-320.
Ruan, X. , and Li, W. (2014, August). Ultrasonic Sensor Based Two-wheeled Self-balancing Robot Obstacle Avoidance Control System, Poster session presented at 2014 IEEE International Conference on Mechatronics and Automation, Tianjin, China.
Saravanan, K. and Mahalakshmi, H. (2013). Brain-Computer Control Of Wheelchair Concluded Mobile Robot. International Journal of Advanced Research in Robotics and Development, 1(1), 1-5.
Savkin, A., V., Wang, C. (2014). Seeking a path through the crowd: Robot navigation in unknown dynamic environments with moving obstacles based on an integrated environment representation. Robotics and Autonomous Systems, 62(10), 1568-1580.
Schaeff, S., Treder, M. S., Venthur, B., and Blankertz, B. (2012). Exploring motion VEPs for gaze-independent communication. Journal of Neural Engineering, 9(4), 045006.
Schmitt, B. M., Münte, T. F., & Kutas, M. (2000). Electrophysiological estimates of the time course of semantic and phonological encoding during implicit picture naming. Psychophysiology, 37(4), 473-484.
Silvoni, S., Konicar, L., Prats-Sedano, M. A., Garcia-Cossio, E., Genna, C., Volpato, C., Cavinato, M., Paggiaro, A., Veser, S., De Massari, D., Birbaumer, N. (2016). Tactile event-related potentials in amyotrophic lateral sclerosis (ALS): Implications for brain-computer interface. Clin Neurophysiol, 127(1), 936-945.
Sluka, K. (2009). A PID Controller For Lego Mindstorms Robots, InPharmix Inc.
Stretton, J., and Thompson, P. J. (2012). Frontal lobe function in temporal lobe epilepsy. Epilepsy Research, 98(1), 1–13
Su, Y., Dai, J., Liu, X., Xu, Q., Zhuang, Y., Chen, W., and Zheng, X. (2010). EEG Channel Evaluation and Selection by Rough Set in P300 BCI. Journal of Computational Information Systems, 6(6), 1727-1735.
Sutton, S., Braren, M., and Zubin, J. (1965). Evoked-potential correlates of stimulus uncertainty. Science, 150(3700), 1187-1188.
Tonin, L., Menegatti, E., Cavinato, M., D’Avanzo, C., Pirini, M., Merico, A., Piron, L., Priftis, K., Silvoni, S., Volpato, C., and Piccione, F. (2009). Evaluation of a robot as embodied interface for brain computer interface systems. International Journal of Bioelectromagnetism, 11(2), 97–104.
Triarhou, L. C. (2006). The signalling contributions of Constantin von Economo to basic, clinical and evolutionary neuroscience. Brain Research Bulletin , 69(3), 223–243.
Vida, A. F. P., Salazar, M. A. O., Lopez, G. S. (2016). Development of a Brain-Computer Interface Based on Visual Stimuli for the Movement of a Robot Joints. IEEE Latin America Transactions, 14(2), 477-484.
Vidal, J. J. (1973, Jan) Toward direct brain-computer communication. Annual Review of Biophysics and Biophysical, 2, 157–80.
Vidal, J. J. (1977, May). Real-time detection of brain events in EEG, Proceedings of the IEEE, 65(5), 633–641.
Wolpaw, J. R., Birbaumer, N., Heetderks, W. J., McFarland,, D. J., Hunter Peckham, P., chalk, G., & Donchin, E. (2000). Brain-Computer Interface Technology: A Review of the First International Meeting. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 8(2), 164-173.
Wolpaw, J. R., Birbaumer, N., McFarland, D. J., Pfurtscheller, G., and Vaughan, T. M. (2002). Brain–computer interfaces for communication and control, Clinical Neurophysiology, 113(6), 767–791.
Wong, C. C., Cheng, C. T., Huang, K. H., Yang Y. T., Chan, H. M. and Yin, C. S. (2009). Obstacle Avoidance Design for Humanoid Robot Based on Four Infrared Sensors. Tamkang Journal of Science and Engineering, 12(3), 249-258.
You, F., Zhang, R., Lie, G., Wang, H., Wen, H., Xu, J. (2015). Trajectory planning and tracking control for autonomous lane change maneuver based on the cooperative vehicle infrastructure system. Expert Systems with Applications, 42(14), 5932–5946.
Zhang, J. X., Fang, Z., Du, Y., Kong, L., Zhang, Q., Xing, Q. (2012). Centro-parietal N200: an event-related potential component specific to Chinese visual word recognition. Chinese Science Bulletin, 57(13), 1516–1532.
Zhang, R., Li, Y., Yan, Y., Zhang, H., Wu, S., Yu, T., and Gu, Z. (2016). Control of a Wheelchair in an Indoor Environment Based on a Brain-Computer Interface and Automated Navigation. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 24(1),128-139.

QRCODE
 
 
 
 
 
                                                                                                                                                                                                                                                                                                                                                                                                               
第一頁 上一頁 下一頁 最後一頁 top