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Pursuit and evasion in a recursive nested behavioral control structure for unmanned aerial vehicles

机译:无人驾驶航空车辆递归嵌套行为控制结构的追求和逃避

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This work tackles the problem of integrating a pursuit-evasion game (PEG) in a recursive nested behavioral control (RNBC) structure for unmanned aerial vehicles (UAV). The UAV agents' architecture is the RNBC structure, considering that the collision avoidance, velocity control and attitude control are already implemented behaviors in this structure. The new high-level behaviors pursuit and evasion are introduced, describing the PEG and providing an appropriate reference velocity vector for the underlying layers of the RNBC structure of the pursuer and the evader, respectively. The reference velocities for the agents are determined by solving the pursuit-evasion problem in a game-theoretical manner, while collision avoidance behavior is implemented one level below. The repulsion force approach is used as collision avoidance technique and provides a velocity vector, which is added to the reference velocity vector of the upper level, if there is a collision risk. The resulting reference input is processed by the subjacent layers in the RNBC structure of the UAV. In simulations it is shown that this approach provides a collision-free pursuit-evasion between UAV agents with dynamic constraints in a general three-dimensional environment with previously unknown obstacles.
机译:这项工作解决了在递归嵌套行为控制(RNBC)结构中整合追求逃避游戏(PEG)的问题,用于无人驾驶飞行器(UAV)。考虑到在该结构中已经实施了碰撞,速度控制和姿态控制,所以无人机的架构是RNBC结构。介绍了新的高级行为追求和逃避,描述了PEG,并分别为追捕者和避难者的RNBC结构的底层提供适当的参考速度载体。代理的参考速度通过以游戏理论方式解决追求逃避问题,而碰撞避免行为在下面实现一个级别。排斥力方法用作碰撞避免技术,并提供速度向量,该速度矢量被添加到上层的参考速度矢量,如果存在碰撞风险。得到的参考输入由UAV的RNBC结构中的子附层处理。在模拟中,表明这种方法在具有先前未知的障碍物的一般三维环境中具有动态约束的无人机之间提供了无人机的无抗追求逃避。

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