Real-time path planning for navigation in unknown environment

T. Wan, Heng Chen, R. Earnshaw
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引用次数: 21

Abstract

Real-time path planning is a challenging task that has many applications in the fields of AI, moving robots, virtual reality, agent behavior simulation, and action games. The various approaches for path planning have different criteria that have to be met, resulting in a number of algorithms for solutions to specific problems. In this paper, we introduce our approach and recent development regarding path planning in game environments. We propose a real-time motion-optimization algorithm called Adaptive Dynamic Points of Visibility (ADPV) for navigation of vehicles or moving agents in dynamical unconfigured environments, which computes a collision-free, time-optimal motion track for the moving objects. Our approach is able to deal with the obstacle-space that is unknown or partially unknown to the moving agent. It therefore solves the drawbacks of traditional obstacle-space configuration methods.
未知环境下导航的实时路径规划
实时路径规划是一项具有挑战性的任务,在人工智能、移动机器人、虚拟现实、智能体行为模拟和动作游戏等领域有着广泛的应用。路径规划的各种方法都有不同的必须满足的标准,这就产生了许多针对特定问题的解决方案算法。在本文中,我们将介绍关于游戏环境中路径规划的方法和最新进展。我们提出了一种实时运动优化算法,称为自适应动态可见点(ADPV),用于车辆或移动主体在动态非配置环境中的导航,该算法计算运动物体的无碰撞、时间最优运动轨迹。我们的方法能够处理移动代理未知或部分未知的障碍物空间。从而解决了传统障碍空间配置方法的弊端。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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