無人地面載具，是一種可以透過遠端遙控或者單晶片微處理器來操控的車輛，本篇論文提出了一個當無人載具行走在一個未知環境下，發現障礙物時，該如何規劃出一條適當的軌跡並追蹤這條軌跡以達到避障的目的。本論文為了加快運算的速度，將使用一種簡化的腳踏車模型來取代一般的車子系統模型，進行系統驗證確認模型的可行性之後，會使用Nonlinear Model Predictive Control(NMPC)，也就是非線性的模型預測控制規劃出適當的行進軌跡以及控制輸入，再由PD cortroller做狀態回授控制，達到避障的效果。並透過CarSim這套軟體所提供的各式的車輛模型，進行模擬後得到模擬的實驗結果。本篇論文的貢獻是將Y-S Yoon期刊[1]第三章的系統模型與控制理論轉換成matlab code及simulink odel，並以CarSim進行動畫模擬已確定結果是否符合預期。
關鍵字:無人載具、路徑規劃、NMPC

SUMMARY
Unmanned Ground Vehicle (UGV) are cars which can controlled by computer or microprocessor. In this thesis, we provide an obstacle avoidance scheme for unmanned ground vehicle as an active safety procedure in unknown environments. This thesis considers two kinds of scenarios, one is that the location of obstacles are known and the full-steps obstacle avoidance method will be used. The other is the location of the bstacles are unknown. Finite-steps obstacle avoidance method will then be used. Both of them use the same method called Nonlinear Model Predictive Control (NMPC). NMPC will generate a safe trajectory via gradient descent method, in which the dynamic model will be replaced by a simplified bicycle model for saving the speed of computing. To make sure the simplified model can generate safe trajectories, we have to validate the model and a PD controller is designed to track the generated trajectory. To obtain safe trajectories in the nonlinear model predictive framework, local obstacle information is incorporated into the cost function using distance based or parallax based method. Results of simulation will be presented by CarSim animation software.
Key word: Trajectory Generation, Nonlinear Model Predictive Control, NMPC, Unmanned Ground Vehicle

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