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Compound locomotion control system combining crawling and walking for multi-crawler multi-arm robot to adapt unstructured and unknown terrain

机译:多履带多臂机器人的爬行与行走相结合的复合运动控制系统,可适应非结构​​化和未知地形

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How to improve task performance and how to control a robot in extreme environments when just a few sensors can be used to obtain environmental information are two of the problems for disaster response robots (DRRs). Compared with conventional DRRs, multi-arm multi-flipper crawler type robot (MAMFR) have high mobility and task-execution capabilities. Because, crawler robots and quadruped robots have complementary advantages in locomotion, therefore we have the vision to combine both of these advantages in MAMFR. Usually, MAMFR (like four-arm four-flipper robot OCTOPUS) was designed for working in extreme environments such as that with heavy smoke and fog. Therefore it is a quite necessary requirement that DRR should have the ability to work in the situation even if vision and laser sensors are not available. To maximize terrains adaption ability, self-balancing capability, and obstacle getting over capability in unstructured disaster site, as well as reduce the difficulty of robot control, we proposed a semi-autonomous control system to realize this compound locomotion method for MAMFRs. In this control strategy, robot can explore the terrain and obtain basic information about the surrounding by its structure and internal sensors, such as encoder and inertial measurement unit. Except that control system also can recognize the relative positional relationship between robot and surrounding environment through its arms and crawlers state when robot moving. Because the control rules is simple but effective, and each part can adjust its own state automatically according to robot state and explored terrain, MRMFRs have better terrain adaptability and stability. Experimental results with a virtual reality simulator indicated that the designed control system significantly improved stability and mobility of robot in tasks, it also indicated that robot can adapt complex terrain when controlled by designed control system.
机译:当仅使用几个传感器即可获取环境信息时,如何提高任务性能以及如何在极端环境中控制机器人是灾难响应机器人(DRR)的两个问题。与传统DRR相比,多臂多鳍式履带式机器人(MAMFR)具有高机动性和任务执行能力。由于履带机器人和四足机器人在运动方面具有互补的优势,因此我们有抱负要在MAMFR中将这两项优势结合起来。通常,MAMFR(类似于四臂四爪机器人OCTOPUS)是为在极端环境下(例如,浓烟和大雾)工作而设计的。因此,即使视力和激光传感器不可用,DRR也应具有在这种情况下工作的能力是非常必要的要求。为了最大化非结构化灾害现场的地形适应能力,自平衡能力和越障能力,并减少机器人控制的难度,我们提出了一种半自治控制系统来实现这种针对MAMFR的复合运动方法。在这种控制策略中,机器人可以探索地形并通过其结构和内部传感器(例如编码器和惯性测量单元)获得有关周围环境的基本信息。除了控制系统还可以通过机器人移动时其手臂和履带的状态来识别机器人与周围环境之间的相对位置关系。由于控制规则简单而有效,并且每个部分都可以根据机器人状态和所探索的地形自动调整其自身状态,因此MRMFR具有更好的地形适应性和稳定性。虚拟现实仿真器的实验结果表明,设计的控制系统显着提高了机器人在任务中的稳定性和机动性,也表明机器人在设计的控制系统控制下能够适应复杂的地形。

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