基于混合感知信息的路径规划模型

针对动态未知环境下的自主虚拟人实时避障问题，提出一种基于混合感知信息的路径规划模型。该模型由全局规划器和局部规划器组成，全局规划器依据已知环境信息先行规划出优化的运动路线，局部规划器通过对人类的规划行为进行分析，建立用于局部动态规划的运动代价评估函数，实现虚拟人在动态未知场景中的智能规划行为。实验结果表明，该模型能保证实时性，模拟符合人类特征的规划 行为。

Path Planning Model Based on Mixed Perception Information

Aiming at the problem of real-time obstacle avoidance for autonomous virtual humans in dynamic unknown environment, this paper presents a path planning model based on the mixed perception information. The model is composed of a global planner and a local planner. The global planner computes an optimal path according to the known environment information, and the local planner establishes the assessment function of motion cost for local dynamic planning according to the analysis of the human planning behavior, realizes the plausible intelligent planning behaviors for virtual humans in dynamic unknown situation. Experimental results show that this model can run in real-time, it can simulate the planning behavior well fitting for human characteristic.