Semantic Segmentation for Object Detection and Grasping with Humanoid Robots

Abstract

Humanoid robots are expected to support to human at environments such as the house hospital, and hotel. For this aim, the humanoid robots should detect and recognize the objects. In this article, semantic segmentation algorithms are proposed to carry out for this aim. Different networks from the literature are used. The simulation results are compared in that accuracy, segmentation performance coefficients and parameter number. The obtained results show that the semantic segmentation is good at this task for the humanoid robots. © 2020 IEEE.