Please use this identifier to cite or link to this item: http://hdl.handle.net/11455/8390
標題: 具有最佳路徑規劃功能的自走式除草機
Design of an Autonomous Lawn Mower with Optimal Route Planning
作者: 徐秉民
Hsu, Ping-Min
關鍵字: path planning
最佳路徑
global positioning system
lawnmower
multi-task planning
全球定位系統
自走式除草機
多工分配
出版社: 電機工程學系所
引用: [1] J. Smith, S. Campbell, J. Morton, “Design and implementation of a control algorithm for an autonomous lawnmower,” IEEE Midwest Symposium on Circuits and Systems, pp. 456-459, 2005. [2] L. Zu , H. Wang, F. Yue, “Localization for robot mowers covering unmarked operational area,” in Proc. of IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 2197-2202, 2004. [3] C. Luo, S. X. Yang, X. Yuan, “Real-time area-covering operations with obstacle avoidance for cleaning robots,” in Proc. of IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 2359-2364, 2002. [4] X. Fan, X. Luo, S. Yi, S. Yang, H. Zhang, “Optimal path planning for mobile robots based on intensified ant colony optimization algorithm,” in Proc. of IEEE International Conference on Robotics, Intelligent Systems and Signal Processing, pp. 131-136, 2000 [5] N. Miyake, T. Aono, K. Fujii, Y. Matsuda, S. Hatsumoto, “Position estimation and path control of an autonomous land vehicle,” in Proc. of IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 690-696, 1997. [6] T. Fukao, H. Nakagawa, N. Adachi, “Adaptive control of a nonholonomic mobile robot,” IEEE Transaction on Robotics and Automation, Vol. 16, No. 5, pp. 609-615, 2000 [7] H. Wang, L. Zu, F. Yue, “Neural networks-based terrain acquisition of unmarked area for robot mowers,” in Proc. of IEEE International Conference on Control, Automation, Robotics and Vision, pp. 735-740, 2004 [8] C. F. Tong, H. Zhang, Y. X. Sun, “Optimal control for a class of chaos synchronization with input constraint,” in Proc. of IEEE International Conference on American Control, pp. 5282-5287, 2006 [9] L. P. Pan, “Linear-nonquadratic optimal control problem with terminal inequality constraints,” Journal of Mathematical Analysis and Application, Vol. 212, pp. 176-189, 1997 [10] D. R. Adams, “Optimal control of the obstacle for a parabolic variational inequality,” Journal of Mathematical Analysis and Application, Vol. 268, pp.602-614, 2002 [11] M. L. Bell, R. W. H. Sargent, “Optimal control of inequality constrained DAE systems,” Journal of Computers and Chemical Engineering, Vol. 24, pp. 2385-2404, 2000 [12] Y. Ye, Q. Chen, “Optimal control of the obstacle in a quasilinear elliptic variational inequality,” Journal of Mathematical Analysis and Application, Vol. 294, pp. 258-272, 2004 [13] W. Wei, J. B. Mbede, Y. Zhang, “Neuro-fuzzy motion control for mobile robot,” in Proc. of IEEE International Conference on Neural Networks, pp. 507-512, 2002 [14] T. Aono, Y. Matsuda, T. Kamiya, K. Seino, “Position estimation using GPS and dead reckoning,” in Proc. of IEEE/SICE/RSJ International Conference on Midtisensor Fusion and Integration for Intelligent Systems, pp. 533-540, 1996 [15] J. Ousingsawat, M. G. Earl, “Modified lawn-mower search pattern for areas comprised of weighted regions,” in Proc. of IEEE International Conference on American Control, pp. 918-923, 2007 [16] Y. C. Tian, M. O. Tadé, D. Levy, “Constrained control of chaos,” Journal of Physics Letters A, Vol. 296, pp. 87-90, 2002 [17] Y. Yamamoto, X. Yun, “Coordinating locomotion and manipulation of a mobile manipulator,” IEEE Transaction on Automatic Control, Vol. 39, No. 6, pp. 1326-1332, 1994 [18] J. M. Yang, J. H. Kim, “Sliding mode control for trajectory tracking of nonholonomic wheeled mobile robots,” IEEE Transaction on Robotics and Automation, Vol. 15, No. 3, pp. 578-587, 1999 [19] Z. Shiller, Y. Fujita, D. Ophir, Y. Nakamura, “Computing a set of local optimal paths through cluttered environments and over open terrain,” in Proc. of IEEE International Conference on Robotics and Automation, pp. 4759-4764, 2004 [20] P. S. Tsai, L. S. Wang, F. R. Chang, “Modeling and hierarchical tracking control of tri-wheeled mobile robots,” IEEE Transaction on Robotics, Vol. 22, No. 5, pp. 1055-1062, 2006 [21] W. Wang, J. Qi, H. Zhang, G. Zong, “A rapid hunting algorithm for multi mobile robots system,” in Proc. of IEEE International Conference on Industrial Electronics and Applications, pp. 1203-1207, 2007 [22] S. Yamaguchi, T. Tanaka, “GPS standard positioning using Kalman filter,” SICE-ICASE International Joint Conference, pp. 1351-1354, 2006 [23] F. Abdessemed, K. Benmahammed, E. Monacelli, “On using evolutionary programming for a mobile robot fuzzy motion controller,” in Proc. of IEEE International Symposium on Intelligent Control, pp. 37-42, 2000 [24] J. E. Naranjo, C. Gonzalez, “Fuzzy logic based lateral control for GPS map tracking,” in Proc. of IEEE Intelligent Vehicles Symposium, pp. 397-400, 2004 [25] R. Chary, R. Nagaraj, G. Raffa, T. S. Cinotti, P. Sebestian, “Sensor-based power management for mobile devices,” in Proc. of IEEE Symposium on Computers and Communications, pp. 263-269, 2006 [26] M. Cong, B. Fang, “Multisensor fusion and navigation for robot mower,” in Proc. of IEEE International Conference on Robotics and Biomimetics, pp. 417-422, 2007 [27] M. Bosse, N. Nourani-Vatani, J. Roberts, “Coverage algorithms for an under-actuated car-like vehicle in an uncertain environment,” in Proc. of IEEE International Conference on Robotics and Automation, pp. 698-703, 2007 [28] C. Luo, S. X. Yang, M. Meng, “Entire region filling in indoor environments using neural networks,” in Proc. of the 4th World Congress on Intelligent Control and Automation, pp. 2039-2044, 2002
摘要: 本論文主要目的在於研發一種自走式除草機,其可結合全球定位系統的功能,提高對於工作區域的操作效率。結合定位系統的自走式除草機可以適用於高爾夫球場等大範圍草地,取代人力,改善傳統除草之工作效率。 本論文主要構想如下:首先建立所需的功能,包含全球定位系統的資料接收與記憶、最佳路徑規劃、障礙迴避、除草路徑導引、初始除草工作地圖設定及障礙位置識別、多工分配等功能。此自走式除草機一開始先以人工推行除草工作邊界和已知障礙邊界完成後,將初始設定結果傳回控制系統,使用者依需要選擇最佳工作路徑,控制系統計算所選之最佳路徑。將求得的除草工作路徑傳回控制面板,令其依路徑開始工作。導引工作期間中,自走式除草機隨時紀錄全球定位系統傳送之除草機位置,遇障礙時,傳回障礙位置座標,控制系統再依預設的方法導引除草機加以迴避。 本論文亦提出一種除草區域多工分配的方法。利用此法,主控系統可以將最佳化工作分配區域傳送給多台自走式除草機,結合多部除草機同步工作的方式,大幅改善單機操作的除草效率。最後經由模擬實驗,證實此路徑規劃方法可以有效改善工作效率。
An optimal path planning scheme for autonomous lawnmowers to achieve minimum working time, minimum energy conservation and mixed operation mode, as well as high efficiency is developed in this thesis. For route planning, rough path planning and a geography method are adopted. A rough path planning is first considered with obstacles ignored. Then, a geography method is applied to enable the details of a real optimal path in accessing the easiest and safest condition. After taking the chosen mode, a distinct path planed on the basis of the obstacles coordinates are obtained. Additionally, a global positioning system (GPS) which provides real-time positioning of the lawnmower is equipped with the path planning system. In addition to the path planning using single mower, an algorithm for multi-task operation as well as the partitioning method for working area is also developed. For this algorithm, we define an index of mowing easiness, with which the accomplishing level in mowing for any prairies can be derived. Based on the figure of mowing easiness, an objective function is proposed for optimization. With the optimization of this objective function, the control law for the optimal multi-task of mowing is developed. The optimal path planning has been tested under a variety of simulations and proven to be effective in enhancing the working efficiency.
URI: http://hdl.handle.net/11455/8390
其他識別: U0005-2907200814293200
文章連結: http://www.airitilibrary.com/Publication/alDetailedMesh1?DocID=U0005-2907200814293200
Appears in Collections:電機工程學系所

文件中的檔案:

取得全文請前往華藝線上圖書館



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.