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Dynamic Obstacle Avoidance in uncertain environment combining PVOs and Occupancy Grid

机译:结合PVO和占用网格的不确定环境中的动态避障

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Most of present work for autonomous navigation in dynamic environment doesn''t take into account the dynamics of the obstacles or the limits of the perception system. To face these problems we applied the probabilistic velocity obstacle (PVO) approach (Kluge and Prassler, 2004) to a dynamic occupancy grid. The paper presents a method to estimate the probability of collision where uncertainty in position, shape and velocity of the obstacles, occlusions and limited sensor range contribute directly to the computation. A simple navigation algorithm is then presented in order to apply the method to collision avoidance and goal driven control. Simulation results show that the robot is able to adapt its behaviour to the level of available knowledge and navigate safely among obstacles with a constant linear velocity. Extensions to non-linear, non-constant velocities are proposed.
机译:在动态环境中的自主导航中的大多数工作并不考虑到障碍物的动态或感知系统的限制。面对这些问题,我们将概率速度障碍(PVO)方法(PVO)方法(Kluge和Prassler,2004)应用于动态占用栅格。本文提出了一种估计碰撞概率的方法,其中障碍物的位置,形状和速度,闭塞和有限的传感器范围直接贡献到计算。然后呈现一个简单的导航算法以应用碰撞避免和目标驱动控制的方法。仿真结果表明,机器人能够将其行为适应可用知识的水平,并安全地在具有恒定线性速度的障碍物中导航。提出了非线性,非恒定速度的延伸部。

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