A sensor fusion approach to improve joint angle and angular rate signals in articulated robots

Abstract

Rotary encoders and resolvers are by far the most common sensors to measure joint angles in articulated robots. Since various control approaches require angular rates as well, resolvers and encoders are also employed to derive angular rate signals. Due to the involved differentiation operation, however, quantization noise may be augmented significantly. Advanced filtering approaches can only partially overcome this drawback. Therefore, direct measurement of angular rates is desirable. Due to advancements in manufacturing technology and pushed by applications in entertainment devices, MEMS gyroscopes have become an attractive alternative for angular rate measurement. Unfortunately, they are affected by bias and other non-negligible disturbances, which may be a serious problem if consistent joint angle and angular rate measurements are required. The proposed approach fuses encoder and angular rate signals to mitigate their major drawbacks - bias and quantization errors - by exploiting their individual strong points. Bias in the angular rate signal is eliminated by analyzing the deviation between the integrated angular rate signal and the encoder signal. Quantization errors in the encoder signal are reduced by a so-called complementary filter which blends the integrated angular rate output with the encoder signal. Apart from a description of the approach and a theoretical analysis of its characteristics, experimental results demonstrating the effectiveness of the approach in closed-loop control of articulated robots are presented.