The widespread application of industrial robots has profoundly reshaped economic development and labor market structures, making it essential to clarify their true impact on income distribution to promote technological transformation and inclusive growth. Drawing on 453 estimates from 32 studies, this paper conducts a meta-regression analysis to systematically examine the effects of industrial robot adoption on income inequality and to identify publication bias and heterogeneity in the existing literature. The results show that industrial robots generally widen income disparities, particularly across urban-rural areas, income groups, and genders, while exhibiting a narrowing effect on inter-industry income gaps. Moreover, significant publication bias is detected, with high-quality journals more inclined to publish studies reporting statistically significant findings. Heterogeneity analysis further indicates that the type of income inequality examined, measurement approaches, robot exposure indicators, and sample sizes all exert substantial influence on reported estimates. By applying advanced meta-regression techniques from economics to the study of industrial robots and income inequality, this paper highlights the sensitivity of research conclusions to measurement choices and sample characteristics, offering valuable methodological guidance for future research.