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Many objects commonly found in household and industrial environments arerepresented by cylindrical and cubic shapes. Thus, it is available for robotsto manipulate them through the real-time detection of elliptic and rectangleshape primitives formed by the circular and rectangle tops of these objects. Wedevise a robust grasping system that enables a robot to manipulate cylindricaland cubic objects in collaboration scenarios by the proposed perceptionstrategy including the detection of elliptic and rectangle shape primitives anddepth information. The proposed method of detecting ellipses and rectanglesincorporates a one-stage detection backbone and then, accommodates the proposedadaptive multi-branch multi-scale net with a designed iterative feature pyramidnetwork, local inception net, and multi-receptive-filed feature fusion net togenerate object detection recommendations. In terms of manipulating objectswith different shapes, we propose the grasp synthetic to align the grasp poseof the gripper with an object's pose based on the proposed detector andregistered depth information. The proposed robotic perception algorithm hasbeen integrated on a robot to demonstrate the ability to carry out human-robotcollaborative manipulations of cylindrical and cubic objects in real-time. Weshow that the robotic manipulator, empowered by the proposed detector, performswell in practical manipulation scenarios.(An experiment video is available inYouTube, https://www.youtube.com/watch?v=Amcs8lwvNK8.)

Real-time Human-Robot Collaborative Manipulations of Cylindrical and Cubic Objects via Geometric Primitives and Depth Information