Deburring of cast parts can be a very challenging task. Today, large burrs on large casting are mostly removed manually. Workers are exposed to hazardous working conditions through, among other things, high noise and vibration levels. Special purpose CNC-machines are available for deburring tasks, but they have a high investment cost that makes them unfit for high-mix low-volume processes. Deburring with robot manipulators are seen as a suitable and less expensive alternative, and have been in the focus of research topic for the last 50 years. Unfortunately, it has failed to move from research into industrial applications. One reason is the long system setup time that makes the cost of automatic deburring too high. This paper deals with the status and usage of robot manipulators in deburring applications with a focus on solutions for cast parts. The deburring pipeline and its components are investigated. There is a special focus on the solutions that lead to a more flexible and automatic deburring system by using sensors such as laser, vision and force control. The solutions are evaluated with regards to the current challenges with robotic deburring and what needs to be improved for robotic deburring to become available for high-mix low-volume processes.
Abstract-The use of vision systems for industrial robot guidance and quality control becomes much harder when the manufactured products and their components are small and possess reflective surface. To assure an effective automated visual inspection of such components, novel solutions are required, able to perform more advanced image analysis and tackle noise and uncertainty. This paper proposes a concept of multi-camera/multi-pose inspection station for star washers inspection, and presents the first results of a functional prototype implementation of it in a robotic cell. The processes of vision-guided part picking from a flexible feeder and closerange inspection in a dedicated rig are described. Solutions for the vision-based tasks of parts identification, machine learningbased classification, circular objects image analysis and star washer teeth segmentation are presented, and further directions are outlined.
Abstract-The widespread use vision systems in robotics introduces a number of challenges related to management of image acquisition and image processing tasks, as well as their coupling to the robot control function. With the proliferation of more distributed setups and flexible robotic architectures, the workflow of image acquisition needs to support a wider variety of communication styles and application scenarios. This paper presents FxIS, a flexible image acquisition service targeting distributed robotic systems with event-based communication.The principal idea a FxIS is in composition of a number of execution threads with a set of concurrent data structures, supporting acquisition from multiple cameras that is closely synchronized in time, both between the cameras and with the request timestamp.
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