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Neural Control with an Artificial Hormone System for Energy-Efficient Compliant Terrain Locomotion and Adaptation of Walking Robots

机译:具有人工激素系统的神经控制,用于节能兼容地形机制和行走机器人的适应

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In order to use walking robots for exploration in a real complex environment, an adaptive control system is required to allow them to successfully and efficiently traverse the terrains. To achieve this, we propose here our adaptive locomotion control technique of a walking robot. It is based on a modular structure, combining neural control with an artificial hormone system. The neural control coordinates all leg joints of the robot and generates its locomotion with various insect-like gaits. In parallel, the artificial hormone system uses the motor commands from the neural control and foot contact feedback to estimate the walking state and automatically adapt the joint movements with respect to the terrain. The adaptability is quickly achieved in an online manner within a few seconds. Robot walking experiments show that this adaptive control technique enables a six-legged robot to adapt to various difficult terrains with energy efficiency. Such terrains include sand (loose ground), sponge with different softness levels (soft/compliant ground), grass (vegetated ground), and floor/pavement (hard ground). The technique does not require robot kinematics or an environmental model; and can, therefore, be potentially applied to different legged robots to achieve stable online adaptation and energy-efficient locomotion on unpredictable (compliant) terrains.
机译:为了在真正的复杂环境中使用行走机器人进行探索,需要一种自适应控制系统来允许它们成功和有效地遍历地形。为实现这一目标,我们在这里提出了我们的自适应机器人控制技术的行走机器人。它基于模块化结构,将神经控制与人工激素系统相结合。神经控制坐标坐标机器人的所有腿部接头,并产生与各种昆虫的仪器的运动。并行地,人工激素系统使用来自神经控制和脚接触反馈的电动机命令来估计行走状态并自动适应相对于地形的关节运动。在几秒钟内以在线方式迅速实现适应性。机器人走路实验表明,这种自适应控制技术使六足机器人能够适应各种难以实现的能量效率。这种地形包括沙子(松动),海绵,具有不同的柔软水平(软/柔软的地面),草(植被地)和地板/路面(硬地)。该技术不需要机器人运动学或环境模型;因此,可以应用于不同的腿机器人,以实现稳定的在线适应和节能运动就是不可预测的(符合要求的)地形。

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