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.
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。
RAPM can abstract the entities in Internet, classify real-time information and get those on the Internet through autonomous perception to build paths.
机器人自主感知模型通过抽象各种网络实体，对网络信息进行分类搜索，自主感知实时的网络传感信息，从而动态规划机器人路径。
They spread like viruses, resistant to the passage of time, in an endless game of mutations where they constantly interfere with the perception of the "real".
在这无穷尽的变异过程中，它们就象病毒一样，不受时空限制，改变人们对肉眼可见的真实世界的传统解读方式。
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