由運動追蹤系統所收集的人體運動資料通常會有許多雜訊，必須先進行處理與修復後才能進行後續應用。本研究完善了本團隊所開發之運動後處理系統，應用了四元數曲線映射的方法將運動資料旋轉項進行平滑處理，使人體運動資料能進行後續分析與應用。
將運動重定向至人形機器人上時，由於受試者與目標幾何尺寸上的不同，重定向後的運動有可能使目標產生自碰撞。本研究建構一套碰撞檢測流程與無自碰撞運動產生流程，以檢測重定向至人形機器人的運動是否有自碰撞。並在自碰撞發生時修改碰撞桿件之運動軌跡，以逆向運動學計算新的人形機器人運動資料。

The purpose of this study is focused on collision detection and self-collision free motion path generation after motion retargeting. At the first, we will introduce our motion data post-process system, iBMPS Post, and the way we deal with rotation motion data. Also, we compare the smoothing result of Fourier transformation and Fourier cosine transformation with same cut-off frequency.
Then we will introduce the data structure for collision detection, axis aligned bounding box tree, include the bounding box characteristic, how to building this data tree by input model and update data tree after model changing position and orientation. In the next chapter, we present our two phase collision detection strategy.
When a pair of link of a humanoid robot model are collide continuously in several timeframe, we mark the beginning and the ending of collision and the timeframe, that two link has maximum interference, as key frame. Then using this three key frame to generate collision free motion path by cubic spline.
We use three motion data to test our method, it works well when links are slightly collision.

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