Abstract: Reconfigurable modular robots feature high mobility due to their unconstrained connection manners. Inspired by the snake multi-joint crawling principle, a chain-type reconfigurable modular robot (CRMR) is designed, which could reassemble into various configurations through the compound joint motion. Moreover, an illumination adaptive modular robot identification (IAMRI) algorithm is proposed for CRMR. At first, an adaptive threshold is applied to detect oriented FAST features in the robot image. Then, the effective detection of features in non-uniform illumination areas is achieved through an optimized quadtree decomposition method. After matching features, an improved random sample consensus algorithm is employed to eliminate the mismatched features. Finally, the reconfigurable robot module is identified effectively through the perspective transformation. Compared with ORB, MA, Y-ORB, and S-ORB algorithms, the IAMRI algorithm has an improvement of over 11.6% in feature uniformity, and 13.7% in the comprehensive indicator, respectively. The IAMRI algorithm limits the relative error within 2.5 pixels, efficiently completing the CRMR identification under complex environmental changes.
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