Robot vision to recognize both object and rotation for robot pick-and-place operation

Abstract

This paper presents a robot vision system to recognize both different target objects and their poses that can be incorporated in robot programming by demonstration (robot PbD). In recent years, robot PbD has become a popular topic in the field of robotics. Programming robots is a time-consuming process and requires technical knowledge. However, robot task programming will be simplified by using a vision system to analyze human demonstration. Usually, design of a user-friendly human-robot interaction interface is crucial to implement the robot PbD process. We take pick-and-place operation as an example of robot PbD. Several objects are placed on a table without overlapping, and people pick one of them to other place, one after another. Before learning from human demonstration, if the robot can obtain initial information, e.g., to recognize the target object and to estimate its pose, it helps robot to refine its following decision, such as selecting the gripper type or the grip angle. Thus the authors develop the robot vision ads the first step to realize such working robot. The developed vision system has advantage of interactive trainability with the help of the proposed graphical user interface (GUI), in which the interpretable features can be easily selected by ordinary users. We also propose a simple scale-invariant pose estimation method. Experimental results support feasibility and effectiveness of the system.

Development of Control System for Dual NC Machine with Single 6-Axis Robot

“…Robot vision systems play an important role in the robot pick-and-place task. They can be used to detect objects, and to measure their location [17]. This vision system is commonly used in industry for a replacement with human eyes because it has the precision technology.…”

Crankshaft-Bearing Assembly Based on Vision-Guided and Attractive Regions in the Environment

“…Accurate pose and position information of industrial parts is a core technology in the application of robot assembly systems, and it is also one of the bottlenecks that restrict the promotion of robots in the customization and personalization in the industrial production field [1]. Visual object localization [2][3] are mainly used to provide pose and position measurement for grasping and assembling. However, when the part and the assembly object are in contact process, it is difficult to obtain a good assembly effect only relying on vision information.…”

“…However, when the part and the assembly object are in contact process, it is difficult to obtain a good assembly effect only relying on vision information. As in crankshaft-bearing assembly, for example, there are also some difficulties: (1)There is a tight fit between the middleware and bearings; (2)It is difficult to predict the contact state of the middleware and the bearing during the assembly process; (3)Because of clamping error and assembly error make it difficult for the crankshaft to be moved to the right above the bearing fit position in the assembly process [4][5].…”