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A potential field and bug compound navigation algorithm for nonholonomic wheeled robots

机译:非完整轮式机器人的潜在场和Bug复合导航算法

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We present a practical trajectory generation algorithm based on the potential field for nonholonomic wheeled robots with obstacle avoidance constraint. The potential field algorithm may be efficient to generate a safe trajectory in realtime. However, it has a drawback to have local minima into which the robot can get trapped. To overcome the drawback, this paper introduces the artificial potential field to force the robot bug-like motion around obstacles. In addition, we discuss the use of the collision cone to generate an efficient repulsive force by reducing effects of previously visited obstacles. The simulation shows the generation of successful trajectories for autonomous robots to satisfy its kinematic constraints.
机译:我们介绍了一种基于具有障碍物避免约束的非完整轮式机器人电位场的实用轨迹生成算法。潜在的场算法可以有效地在实时生成安全轨迹。然而,它有一个缺点是具有局部最小值,机器人可以被捕获到其中。为了克服缺点,本文介绍了人工潜在领域,以迫使机器人的臭虫类似障碍物的运动。此外,我们讨论碰撞锥体通过减少先前访问的障碍物的效果来产生有效的排斥力。该模拟显示了自主机器人成功轨迹的产生,以满足其运动的约束。

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