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Adaptive Robust Three-dimensional Trajectory Tracking for Actively Articulated Tracked Vehicles

机译:主动铰接履带车辆的自适应鲁棒三维轨迹跟踪

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摘要

A new approach is proposed for an adaptive robust three-dimensional (3D) trajectory-tracking controller design. The controller is modeled for actively articulated tracked vehicles (AATVs). These vehicles have active sub-tracks, called flippers, linked to the ends of the main tracks, to extend the locomotion capabilities in hazardous environments, such as rescue scenarios. The proposed controller adapts the flippers configuration and simultaneously generates the track velocities, to allow the vehicle to autonomously follow a given feasible 3D path. The approach develops both a direct and differential kinematic model of the AATV for traversal task execution correlating the robot body motion to the flippers motion. The benefit of this approach is to allow the controller to flexibly manage all the degrees of freedom of the AATV as well as the steering. The differential kinematic model integrates a differential drive robot model, compensating the slippage between the vehicle tracks and the traversed terrain. The underlying feedback control law dynamically accounts for the kinematic singularities of the mechanical vehicle structure. The designed controller integrates a strategy selector too, which has the role of locally modifying the rail path of the flipper end points. This serves to reduce both the effort of the flipper servo motors and the traction force on the robot body, recognizing when the robot is moving on a horizontal plane surface. Several experiments have been performed, in both virtual and real scenarios, to validate the designed trajectory-tracking controller, while the AATV negotiates rubble, stairs, and complex terrain surfaces. Results are compared with both the performance of an alternative control strategy and the ability of skilled human operators, manually controlling the actively articulated components of the robot.
机译:提出了一种新的自适应鲁棒三维(3D)轨迹跟踪控制器设计方法。该控制器针对主动铰接式履带车辆(AATV)建模。这些车辆具有活动的子轨道,称为鳍状肢,链接到主轨道的末端,以扩展危险环境(例如救援场景)中的运动能力。拟议中的控制器采用鳍状肢的配置,并同时生成履带速度,以使车辆能够自主地遵循给定的可行3D路径。该方法开发了AATV的直接运动学模型和差分运动学模型,用于遍历任务执行,将机器人的身体运动与脚蹼的运动相关联。这种方法的好处是允许控制器灵活地管理AATV的所有自由度以及转向。差分运动学模型集成了差分驱动机器人模型,可补偿车辆轨迹和行驶的地形之间的滑移。潜在的反馈控制律动态地说明了机械车辆结构的运动学奇点。所设计的控制器也集成了策略选择器,该策略选择器的作用是局部修改鳍状肢端点的轨道。通过识别机器人何时在水平面上运动,这可以减少挡板伺服电机的工作量和对机器人主体的牵引力。在AATV协商碎石,楼梯和复杂地形表面的同时,已经在虚拟和真实场景中进行了一些实验,以验证设计的轨迹跟踪控制器。将结果与替代控制策略的性能和熟练的人工操作员手动控制机器人主动铰接组件的能力进行比较。

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  • 来源
    《Journal of Field Robotics》 |2016年第7期|901-930|共30页
  • 作者单位

    ALCOR Laboratory, DIAG A. Ruberti, Sapienza University of Rome, Via Ariosto 25, 00185, Rome;

    ALCOR Laboratory, DIAG A. Ruberti, Sapienza University of Rome, Via Ariosto 25, 00185, Rome;

    ALCOR Laboratory, DIAG A. Ruberti, Sapienza University of Rome, Via Ariosto 25, 00185, Rome;

    ALCOR Laboratory, DIAG A. Ruberti, Sapienza University of Rome, Via Ariosto 25, 00185, Rome;

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