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首页> 外文期刊>Journal of robotic systems >Neural Virtual Sensors for Terrain Adaptation of Walking Machines
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Neural Virtual Sensors for Terrain Adaptation of Walking Machines

机译：用于步行机地形适应的神经虚拟传感器

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When walking in realistic conditions, accurate, reliable sensorial information is critical to ensure the safe operation of legged robots. That means a large number of sensors, cabling, and electronic systems must be used, complicating the robot. On the other hand, the great complexity of the hardware of walking machines is one of the main obstacles preventing the introduction of this kind of vehicle in real applications; consequently this hardware should be simplified. These antagonistic requirements can be reconciled by the use of what are called virtual sensors. This paper addresses the design of virtual sensors for terrain adaptation developed with the aims of simplifying the hardware of the walking machine or increasing the reliability of the sensorial information available. These virtual sensors are based on neural networks and can estimate the forces exerted by the feet from data extracted from joint-position sensors, which are mandatory in all robotic systems. The force estimates are used to detect foot/ground contact. Some experiments carried out with the SILO4 walking robot are reported to prove the efficacy of this method.
机译：在现实条件下行走时，准确，可靠的传感信息对于确保有腿机器人的安全操作至关重要。这意味着必须使用大量的传感器，电缆和电子系统，从而使机器人复杂化。另一方面，步行机硬件的高度复杂性是阻碍将这种车辆引入实际应用的主要障碍之一。因此，应简化此硬件。这些对抗性要求可以通过使用所谓的虚拟传感器来解决。本文介绍了用于地形适应的虚拟传感器的设计，其目的是简化步行机的硬件或提高可用的传感信息的可靠性。这些虚拟传感器基于神经网络，可以从关节位置传感器提取的数据中估计脚所施加的力，这在所有机器人系统中都是必不可少的。力估计值用于检测脚/地面接触。据报道，使用SILO4步行机器人进行的一些实验证明了该方法的有效性。

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