Color Recognition for Rubik's Cube Robot

In this paper, we proposed three methods to solve color recognition of Rubik's cube, which includes one offline method and two online methods. Scatter balance & extreme learning machine (SB-ELM), an offline method, is proposed to illustrate the efficiency of training based method. We also put forward a conception of color drifting which indicates offline methods are always ineffectiveness and can not work well in continuous change circumstance. By contrast, weak label hierarchic propagation is proposed for unknown all color information but only utilizes weak label of center block in color recognition. Furthermore, dynamic weight label propagation, another online method, is also proposed for labeling blocks color by known center blocks color of Rubik's cube. We finally design a Rubik's cube robot and construct a dataset to illustrate the efficiency and effectiveness of our online methods and to indicate the ineffectiveness of offline method by color drifting in our dataset.

I. Introduction

Rubik’s cube puzzle has continually been as a hot topic in intelligence competition for child or adult. In service robot fields, however, the solution of Rubik’s cube puzzle in efficient manner is a very challenging task for computer vision. A software scheme to solve Rubik’s cube puzzle includes detection, color recognition and solve method of a randomly scramble cube. Rubik’s cube puzzle can be also considered as a sequential manipulation problem for service robot [1]. For example, to achieve a higher precise sequential manipulation, an optical time-of-flight pre-touch sensor which used for grasping Rubik’s cube is proposed in [2]. Fig. 1.

Cube-solving Robot