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:2019,28(7):101-108
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基于马尔可夫决策过程的群体动画运动轨迹生成
(北京工业大学 信息学部 计算机学院, 北京 100124)
Motion Trajectory Generating Algorithm Based on Markov Decision Processes for Crowd Animation
(College of Computer Science, Faculty of Information Technology, Bejing University of Technology, Bejing 100124, China)
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投稿时间:2019-01-10    修订日期:2019-02-03
中文摘要: 近些年来,群体动画在机器人学、电影、游戏等领域得到了广泛的研究和应用,但传统的群体动画技术均涉及复杂的运动规划或碰撞避免操作,计算效率较低.本文提出了一种基于马尔可夫决策过程(MDPs)的群体动画运动轨迹生成算法,该算法无需碰撞检测即可生成各智能体的无碰撞运动轨迹.同时本文还提出了一种改进的值迭代算法用于求解马尔可夫决策过程的状态-值,利用该算法在栅格环境中进行实验,结果表明该算法的计算效率明显高于使用欧氏距离作为启发式的值迭代算法和Dijkstra算法.利用本文提出的运动轨迹生成算法在三维(3D)动画场景中进行群体动画仿真实验,结果表明该算法可实现群体无碰撞地朝向目标运动,并具有多样性.
Abstract:Crowd animation has been researched and applied in many domains in recent years, such as robotics, movies, games, and so on. But the traditional technologies for creating crowd animation all need complex calculating for motion planning or collision avoidance, the computing efficience is low. This paper presents a new algorithm for generating motion trajectory based on Markov Decision Processes (MDPs) for crowd animation, it can generate all agents' collision-free motion trajectories without any collision detecting. At the same time, this paper presents a new improved value iteration algorithm for solving the state-values of MDPs. We test the performance of the new improved value iteration algorithm on grid maps, the experimental results show that the new alogithm outperforms the value iteration algorithm using Euclidean distance as heuristics and Dijkstra algorithm. The results of crowd animation simulating experiments using the motion trajectory generating algorithm in three-dimensional (3D) scenes show that the proposed motion generating algorithm can make all agents move to the goal position without any collision, meanwhile, agents' motion trajectories are different when we run the algorithm at different time and this effect makes the crowd animation much more alive.
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刘俊君,杜艮魁.基于马尔可夫决策过程的群体动画运动轨迹生成.计算机系统应用,2019,28(7):101-108
LIU Jun-Jun,DU Gen-Kui.Motion Trajectory Generating Algorithm Based on Markov Decision Processes for Crowd Animation.COMPUTER SYSTEMS APPLICATIONS,2019,28(7):101-108

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