To improve the dynamic characteristic of two-axis force sensors, a dynamic compensation method is proposed. The two-axis force sensor system is assumed to be a first-order system. The operation frequency of the system is expanded by a digital filter with backward difference network. To filter high-frequency noises, a low-pass filter is added after the dynamic compensation network. To avoid overcompensation, parameters of the proposed dynamic compensation method are defined by trial and error. Step response methods are utilized in dynamic calibration experiments. Compared to experiment data without compensation, the response time of the dynamic compensated data is reduced by 30%~40%. Experiments results demonstrate the effectiveness of our method. 1. Introduction Multiaxis robot wrist force sensors are necessary for robotic systems in which contact force information between robots and environments needs to be obtained. There are various kinds of multiaxis force sensors available in commercial and research area, for example, cross-beam type multiaxis force sensors [1, 2], piezoelectric multiaxis force sensors , fiber multiaxis force sensors , and so on . Multiaxis robot wrist force sensors are always mounted on the wrists of robots to convert multidimensional contact force signals into multichannel voltage signals. Such kinds of applications can be frequently found in assemble robots, teleoperation robotic systems, rehabilitation robots, and so forth [6–9]. During a robot task, the effectiveness of on-line force perception and feedback highly relies on the performances of the multiaxis robot wrist force sensor. The strong real time and rapidity in robot tasks require multiaxis force sensors to perform high dynamic characteristic. However, multiaxis force sensors (hereafter referred to as “force sensors”) always have low natural frequency and small damping ratio owing to the low stiffness of elastic body and using of strain gauges. As a result, the dynamic response of the force sensors is more than 0.2？ms, and the adjusting time is relatively long . The A/D converters for force sensors will prolong the response time as well. The disparity of dynamic requirements from robotic tasks and the current performances of force sensors motivate the need to improve dynamic characteristics of force sensors. Improving dynamic characteristic of force sensors by hardware is limited and costly. In the field of measurement, dynamic performances of sensors are often improved by algorithms. Hence, dynamic compensation algorithms need to be designed to improve
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