PUBLICATIONS

AUTHORS: E. Ozturk, A. Barrios, C. Sun, S. Rajabi, J. Muñoa

Robotic Assisted Milling for Increased Productivity

Robots’ role in machining is growing as they are being used as machining platforms in increasing number of applications. Moreover, robots have an important role in a new application called, robotic assisted milling, where a robot provides additional support to a workpiece when actual machining is performed by a machine tool. In the paper, alternative methods of support with the robot, i.e. fixed and mobile support are explained. Experimental results show that the robot’s support improves the static and dynamic response of the process. Hence, dimensional errors are minimized and surface quality is improved.

26 April 2018

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AUTHORS: W. Ji, Y. Wang, H. Liu, L. Wang 

Interface Architecture Design for Minimum Programming in Human-Robot Collaboration 

Many metal components, especially large-sized ones, need to be ground or deburred after turning or milling to improve the surface qualities, which heavily depends on human interventions. Robot arms, combining movable platforms, are applied to reduce the human work. However, robots and human should work together due to the fact that most of the large-sized parts belong to small-batch products, resulting in a large number of programming for operating a robot and movable platform. Targeting the problem, this paper proposes a new interface architecture towards minimum programming in human-robot collaboration. Within the context, a four-layer architecture is designed: user interface, function block (FB), functional modules and hardware. The user interface is associated with use cases. Then, FB, with embedded algorithms and knowledge and driven by events, is to provide a dynamic link to the relevant application interface (APIs) of the functional modules in terms of the case requirements.

13 Mar 2018

AUTHORS: S. Garnier, K. Subrin, P. Arévalo-Siles, G. Caverot, B. Furet

Mobile Robot Stability for Complex Tasks in Naval Industries 

Naval industries are looking for new ways to perform complex tasks on large and stationary parts. In this context, mobile manipulator which consists of a robot manipulator mounted on a wheeled base (Automated Guided Vehicle) is a promising solution. In order to guaranty the quality and free the workers to make dangerous or repetitive tasks, the manufacturing process is redefined where the worker supervises and collaborates with the robotic system. In this paper, the stability of such a robotic system is studied in a dynamic way for a better understanding of the stability of robotic system in order it to be a safe solution. Various representations are given to understand the influence of joint speed and joint acceleration. Finally, as a Key Performance Indicator, a map is drawn to represent the effect of the structure height on the tip-over.

10 Mar 2018

AUTHORS: W. Ji, L. Wang

Industrial Robotic Machining:
a review

For the past three decades, robotic machining has attracted a large amount of research interest owning to the benefit of cost efficiency, high flexibility and multi-functionality of industrial robot. Covering articles published on the subjects of robotic machining in the past 30 years or so; this paper aims to provide an up-to-date review of robotic machining research works, a critical analysis of publications that publish the research works, and an understanding of the future directions in the field. The research works are organised into two operation categories, low material removal rate (MRR) and high MRR, according their machining properties, and the research topics are reviewed and highlighted separately. Then, a set of statistical analysis is carried out in terms of published years and countries. Towards an applicable robotic machining, the future trends and key research points are identified at the end of this paper.

3 Apr 2019

AUTHORS: N. A.Theissen, T. Laspas, A. Archenti

Closed-force-loop Elastostatic Calibration of Serial Articulated Robots

This paper presents a novel methodology to measure the compliance of articulated serial robots based on the Elastically Linked Systems concept. The idea behind the methodology is to measure serial articulated robots with customized external wrench vectors under a closed-force-loop. The methodology proposes to measure robots in use-case defined configurations to increase the effect of the identified model parameters on their later implementation. The measurement methodology utilizes the Loaded Double Ball Bar to customize wrench vectors and a laser tracker to measure the system response. In particular, the Loaded Double Ball Bar creates the closed-force-loop to create a flow of forces similar to the intended application of the robot. The methodology is applied to an industrial robot with six rotary joints using the LDBB and a laser tracker. Finally, the paper ends on a discussion about the implementation of the model parameters to improve the accuracy of robots as well as challenges to realize a more cost efficient elastostatic calibration.

Jun 2019

AUTHORS: A. Fabisch

Pytransform3d:
3D Transformations
for Python

Pytransform3d is a Python library for transformations in three dimensions. Heterogenous software systems that consist of proprietary and open source software are often combined when we work with transformations. For example, suppose you want to transfer a trajectory demonstrated by a human to a robot. The human trajectory could be measured from an RGB-D camera, fused with inertial measurement units that are attached to the human, and then translated to joint angles by inverse kinematics. That involves at least three different software systems that might all use different conventions for transformations. Sometimes even one software uses more than one convention.

31 Jan 2019

AUTHORS: A. Verl, A. Valente, S. Melkote, C. Brecher, E. Ozturk, L. T. Tunc

Robots
in Machining

Robotic machining centers offer diverse advantages: large operation reach with large reorientation capability, and a low cost, to name a few. Many challenges have slowed down the adoption or sometimes inhibited the use of robots for machining tasks. This paper deals with the current usage and status of robots in machining, as well as the necessary modelling and identification for enabling optimization, process planning and process control. Recent research addressing deburring, milling, incremental forming, polishing or thin wall machining is presented. We discuss various processes in which robots need to deal with significant process forces while fulfilling their machining task.

9 May 2019

AUTHORS: C. Sun, Patrick L.F. Kengne, A. Barrios, S. Mata, E. Ozturk

Form Error Prediction
in Robotic Assisted Milling

Robotic assisted milling is a process where a robot supports a workpiece while a machine tool cuts the workpiece. It can be used to suppress vibrations and minimize form errors in thin wall workpieces. In this paper, form error on a workpiece is simulated using a static force model, a frequency domain model and a hybrid model while a robot supports the workpiece from the other side. Machining results show that assistance of the robot has a considerable effect of the magnitude of form errors. Hence, support force should be carefully selected by simulation before machining. Finally, simulation results show that hybrid model gives the best fit among those three models.

Apr 2019

AUTHORS: M. Terreran, M. Antonello, S. Ghidoni

Boat Hunting with Semantic Segmentation for Flexible and Autonomous Manufacturing

Customized mass production of boats and other vehicles requires highly complex manufacturing processes that need a high amount of automation. To enhance the efficiency of such systems, sensing is of paramount importance to provide robots with detailed information about the working environment. In this paper, we propose the use of semantic segmentation to detect the key elements involved in production, to boost automation in the production process. Our main focus is on the sanding process of these tools by means of a robot. We demonstrate the potential of these techniques in an industrial environment featuring a lower degree of variability with respect to the domestic scenes typically considered in the literature. In the production environment, however, higher performances are required to address challenging manufacturing operations successfully. In this work, we also show that exploiting contextual cues and multiple points of view can further boost the reliability of our system, which provides useful data to the other robot modules in charge of navigation, work station recognition, and other tasks. 

4-6 September 2019