UKF-Based Sensor Fusion Method for Position Estimation of a 2-DOF Rope Driven Robot

Myeongjin Choi,Hwa Soo Kim,Myoungjae Seo,Taewon Seo

doi:10.1109/access.2021.3051404

Myeongjin Choi, Hwa Soo Kim + Show 2 more

Open Access

https://doi.org/10.1109/access.2021.3051404

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Abstract

In this study, the unscented Kalman filter-based method was introduced as a new technique for position estimation of the two-degree-of-freedom facade cleaning robot known as the Dual Ascender Robot (DAR). While other facade cleaning robots use a winch, the DAR uses an ascender, resulting in rope slip inside the ascender. Rope slip does easily cause errors in length data, so DARs cannot be easily controlled based on length data as in the case of most facade cleaning robots. Therefore, the DARs estimate the length data and use it through position estimation to overcome the rope slip for control. DARs use a rope length-based sensor fusion method for position estimation. This method employs position data based on both length data and angle data to estimate the position; however, it is difficult to use for long periods of time owing to the increased error that accumulates with time. Therefore, the use of position data based on angle data is proposed herein via application of the unscented Kalman filter. This unscented Kalman filter-based method is tested to confirm that the positional estimation performance is improved relative to that achieved via the previously used method. The performance improvements are compared in terms of accuracy and repeatability using the double ball bar method, and the errors in accuracy and repeatability are found to be reduced by approximately 2–3 times.

Highlights

Buildings of increased heights are being constructed to use space efficiently in cities
The results demonstrate that the rope angle-based Kalman filter method was better than the sensor fusion method in terms of repeatability
In this study, a new position estimation method, the Kalman filter method based on rope angle data, was proposed and applied to the Dual Ascender Robot (DAR)

Summary

INTRODUCTION

Buildings of increased heights are being constructed to use space efficiently in cities. Façade cleaning robots with more than 2 DOFs using rope employ a mechanical device called a winch that winds and releases the rope; changes in the rope length are not caused because the end points are fixed when the robot is installed on the building, as shown in Fig. 1 (a). Each time the rope is wound and released inside the ascender, rope slip occurs and a change in the rope length is caused, as shown in Fig. 1 (b) This implies that the DAR cannot use the control method that most 2-DOF façade cleaning robots use. In the sensor fusion method, a cumulative error in position estimation is obtained on using the error rope length; the rope angle-based Kalman filter method is suitable for use in DARs because it can capture the rope length error through filtering. As with the position data based on the angle data, the angle θi of the robot is varied to the rope length li in Eq (1)

POSITION ESTIMATION

KALMAN FILTER METHOD ON DAR

EXPERIMENT RESULTS

CONCLUSION