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Controlling Off-Road Bi-steerable Mobile Robots: An Adaptive Multi-control Laws Strategy

机译:控制越野双转向移动机器人:自适应多控制律策略

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This paper proposes a path tracking strategy for wheeled mobile robots of type {1,2} (i.e. equipped with two steering axles), with the aim to ensure the convergence of the front and rear control points along a same trajectory, leading to reduce the required space to achieve maneuvers. The proposed approach considers front and rear steering axles as two separate systems with their own control variables: the front and the rear steering angles. The problem of managing two steering axles is solved without considering an explicit control of the robot's orientation, nor a relationship between the two steering angles which is generally a not optimal approach. The proposed control laws are based on adaptive and predictive control techniques in order to address phenomena acting when moving in unstructured context, such as bad grip conditions, low-level and inertial delays. As a result, this control algorithm enables to accurately control bi-steerable mobile robots, while increasing their maneuverability. This is particularly suitable for off-road applications, such as in agriculture where potentially large robots have to move in cluttered environments and face low grip conditions.
机译:本文为{1,2}型轮式移动机器人(即配备两个转向轴)提出了一种路径跟踪策略,目的是确保前后控制点沿同一轨迹会聚,从而减少实现机动所需的空间。所提出的方法将前转向轴和后转向轴视为具有各自控制变量的两个独立系统:前转向角和后转向角。解决了管理两个转向轴的问题,而无需考虑对机器人方向的明确控制,也无需考虑通常不是最佳方法的两个转向角之间的关系。提出的控制律是基于自适应和预测控制技术的,目的是解决在非结构化环境中运动时发生的现象,例如不良的抓地力条件,低水平和惯性延迟。结果,该控制算法能够在增加可操纵性的同时,精确地控制可双向操纵的移动机器人。这特别适用于越野应用,例如在农业中,潜在的大型机器人必须在混乱的环境中移动并面临低抓地力条件。

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