In this article, we shall introduce a novel technique for order preference by similarity to ideal solution (TOPSIS)-based methodology to resolve multicriteria group decision-making problems within picture fuzzy environment, where the weights information of both the decision makers (DMs) and criteria are completely unknown. First, we briefly review the definition of picture fuzzy sets (PFS), score function and accuracy function of PFRSs and their basic operational laws. In addition, defined the generalized distance measure for PFRSs based on picture fuzzy rough entropy measure to compute the unknown weights information. Secondly, the picture fuzzy information based decision-making technique for multiple attribute group decision making (MAGDM) is established and all computing steps are simply depicted. In our presented model, it's more accuracy and effective for considering the conflicting attributes. Finally, an illustrative example with robot selection is provided to demonstrate the effectiveness of the proposed picture fuzzy decision support approaches, together with comparison results discussion, proving that its results are feasible and credible.