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Geometric Region-Based Swarm Robotics Path Planning in an Unknown Occluded Environment

机译:基于几何地区的群体机器人路径规划在未知的遮挡环境中

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This article presents a geometrical region-based shape control methodology for navigating a cohesive swarm-robotic structure toward the goal even in a field occluded by unknown obstacles. In this control approach, initially, the robotic swarm is conceived to lie within a well-defined virtual circular region thus preserving a strict interagent cohesiveness among them. However, during the progression, for evading severely constricted obstacles, the virtual circle has been allowed to change its shape and in the process, varied elliptical shapes are made to evolve. In essence, for a collision-free solution, this shrinking aspect (from circle to ellipse) depends entirely on the number of agents in the swarm and at the same time also reliance on the sensed distance between two nearest obstacles through which the shrunken circle or the virtual ellipse will be able to pass. Consequently, shape switching is a dynamic as well as a stochastic process throughout the journey of the swarm. For achieving these objectives, a two-level hierarchical control strategy has been employed. Moreover, during aggregating toward the target, the actuation failure of any agent or agents may occur. In this perspective, the proposed control law has been updated adaptively throughout the route such that agent failure does not encumber the mission. Finally, the extensive simulation results along with the hardware experimentation are provided to demonstrate the efficacy of the proposed scheme.
机译:本文提出了一种基于几何区域的形状控制方法,用于导航到目标的粘性群机器人结构,即使在由未知障碍物堵塞的场上也是如此。在该控制方法中,最初,构思机器人群地区在明确明确的虚拟圆形区域内,从而保持它们之间的严格的互动凝聚力。然而,在进展期间,为了逃避严重限制的障碍物,已经允许虚拟圆圈改变其形状和在过程中,使变化的椭圆形形状变化。实质上,对于无碰撞解决方案,这种收缩方面(从圆形到椭圆)完全取决于群体中的代理数量,同时也依赖于两个最接近障碍物之间的感测距离,通过该距离缩小圈或虚拟椭圆将能够通过。因此,在整个群体的旅程中,形状切换是一种动态的和随机过程。为了实现这些目标,采用了两级分层控制策略。此外,在朝向目标的聚集期间,可能发生任何药剂或药剂的致动失效。在这种观点中,拟议的控制法已在整个路线中自适应更新,使得代理失败不会妨碍特派团。最后,提供了广泛的仿真结果以及硬件实验的结果以证明所提出的方案的功效。

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