We propose a methodology based on reservoir computing for mapping local proprioceptive information acquired at the level of the leg joints of a simulated quadruped robot into exteroceptive and global information, including both the ground reaction forces at the level of the different legs and information about the type of terrain traversed by the robot. Both dynamic estimation and terrain classification can be achieved concurrently with the same reservoir computing structure, which serves as a soft sensor device. Simulation results are presented together with preliminary experiments on a real quadruped robot. They demonstrate the suitability of the proposed approach for various terrains and sensory system fault conditions. The strategy, which belongs to the class of data-driven models, is independent of the robotic mechanical design and can easily be generalized to different robotic structures.

中文翻译：

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用于估计四足机器人本体感觉状态的外感觉条件的回声状态网络。

我们提出了一种基于水库计算的方法，用于将在模拟四足机器人腿关节水平获得的局部本体感觉信息映射到外部和全局信息，包括不同腿水平的地面反作用力和有关类型的信息机器人穿越的地形。动态估计和地形分类可以通过相同的储层计算结构同时实现，作为软传感器设备。仿真结果与真实四足机器人的初步实验一起呈现。他们证明了所提出的方法适用于各种地形和传感系统故障条件。该策略属于数据驱动模型类，