Abstract: Combined with motion capture and dynamic simulation, characters in animation have realistic motion details and can respond to unexpected contact forces. This paper proposes a novel and real-time character motion generation approach which introduces a parallel process, and uses an approximate nearest neighbor optimization search method. Besides, we employ a support vector machine (SVM), which is trained on a set of samples and predicts a subset of our "return-to" motion capture (mocap) database in order to reduce the search time. In the dynamic simulation process, we focus on designing a biomechanics based controller which detects the balance of the characters in locomotion and drives them to take several active and protective responses when they fall to the ground in order to reduce the injuries to their bodies. Finally, we show the time costs in synthesis and the visual results of our approach. The experimental results indicate that our motion generation approach is suitable for interactive games or other real-time applications.