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SoPC-Based Adaptive Motion Control, Optimal Configurations and Global Path Planning for Three-Wheel Omnidirectional Mobile Service Robot
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本論文旨在發展植基於系統可程式晶片(SoPC)的三輪全方位行動服務機器人之適應運動控制、最佳組態和全域路徑規劃。卡氏座標空間和極座標空間的適應運動控制器經由適應倒逆步法被合成出來，並完成軌跡追踨和穩定。更進一步的，一個平行DNA演算法 (PDNA) 和平行精英基因演算法 (PEGA) 被發展來解決全方位機器人的冗餘問題和全域路徑規劃問題。一個coarse-grain平行化模型不僅被用在PDNA演算法求解全方位行動服務機器人的最佳組態問題並執行滅火任務，而且也用在PEGA求解全域路徑規劃問題。被發展出來的二個適應運動控制器、PDNA演算法、PEGA也都有效的利用硬體/軟體 協同設計和SoPC技術植基於FPGA晶片內。可重覆使用的IP (Intellectual Property) 元件庫也快速的在FPGA內發展出來並整合同一晶片內的嵌入式處理器和嵌入式即時作業系統，驅動行動機器人追踨軌跡和解決行動機器人的最佳化問題。經由模擬和實驗結果，這二個植基於SoPC 的卡氏座標和極座標的適應動態控制器比傳統的全方位行動平台控制器性能更好。更進一步的，植基於SoPC所發展出來的PDNA 演算法和PEGA 也被證明能更有效的解決最佳化的問題。本論文所提出來的技術能夠提供在自主性行動機器領域的研究中，值得參考的方法。
This dissertation presents SoPC-based embedded adaptive motion controllers in both Cartesian and polar coordinates, optimal configuration, and global path planning for three-wheel omnidirectional mobile service robot. The adaptive Cartesian-space and polar-space motion controllers are synthesized via adaptive backstepping to achieve both trajectory tracking and stabilization. Moreover, a parallel deoxyribonucleic acid (PDNA) algorithm and a parallel elite genetic algorithm (PEGA) are presented to solve the redundant inverse kinematic problem and global path planning problem for the omnidirectional mobile robot. A coarse-grain parallel model is not only used to the PDNA algorithm for optimal configurations of an omnidirectional mobile service robot performing fire extinguishment task, but also applied to the PEGA for global path planning. The proposed two adaptive motion controllers, coarse-grain PDNA algorithm and PEGA have been efficiently implemented into field-programmable gate array (FPGA) chips using the hardware/software co-design technique and SoPC (System-on-a-Programmable-Chip) technique. The reusable IP (Intellectual Property) core library has been rapidly developed in FPGA chips by incorporating with the embedded processor and the real-time operating system (RTOS) in the same chip to drive the mobile robot to follow the desired trajectory and solving the optimal problems for omnidirectional mobile robot. Through simulations and experimental results, the proposed SoPC-based adaptive controllers in both Cartesian and polar space outperform conventional controllers for three-wheel omnidirectional mobile platform. Furthermore, the proposed SoPC-based PDNA algorithm and PEGA are shown more powerful to solve the optimal problems. The proposed techniques may provide useful references for professionals working in the field of autonomous mobile robotics.
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