To function autonomously in the physical world, humanoid robots need high-fidelity sensing systems, especially for forces that cannot be easily modeled. Modeling forces in robot feet is particularly challenging due to static indeterminacy, thereby requiring direct sensing. Unfortunately, resolving forces in the feet of some smaller-sized humanoids is limited both by the quality of sensors and the current algorithms used to interpret the data. This paper presents light-weight, low-cost and open-source force-sensing shoes to improve force measurement for popular smaller-sized humanoid robots, and a method for calibrating the shoes. The shoes measure center of pressure (CoP) and normal ground reaction force (GRF). The calibration method enables each individual shoe to reach high measurement precision by applying known forces at different locations of the shoe and using a regularized least squares optimization to interpret sensor outputs. A NAO robot is used as our experimental platform. Experiments are conducted to compare the measurement performance between the shoes and the robot's factory-installed force-sensing resistors (FSRs), and to evaluate the calibration method over these two sensing modules. Experimental results show that the shoes significantly improve CoP and GRF measurement precision compared to the robot's built-in FSRs. Moreover, the developed calibration method improves the measurement performance for both our shoes and the built-in FSRs.
翻译:为了在物理世界中自主运作,人体机器人需要高纤维感测系统,特别是无法轻易建模的力量。机器人脚部的建模力量由于静态的不确定性而特别具有挑战性,因此需要直接感测。不幸的是,在一些较小体型人类的脚部中,解析力量受到传感器质量和当前用于解释数据的算法的限制。本文提供了轻量、低成本和开源的威力感测鞋,以改进流行的小型人体机器人的威力测量,以及校准鞋的方法。压力和正常地面反应力的鞋测量中心(CoP)和正常的地面反应力(GRF)。校准方法使每个人的鞋都能够达到高测量精度,在不同地点运用已知的力量,并使用固定的最小平方优化来解释传感器输出。使用NAO机器人作为我们的实验平台。进行了实验,以比较鞋和机器人的工厂威力测量器(FSRs)的测量性能,并评估这两个感测模型的校准方法的校准方法。实验性结果显示,将GPS的精确度测量方法与GRS的精确度测量方法都大大改进。