Human Assisted Computer Vision on Industrial Mobile Robots (original) (raw)

7 Improving Accuracy and Flexibility of Industrial Robots Using Computer Vision

2012

A high level of positioning accuracy is an essential requirement in a wide range of industrial robots’ applications. Robot calibration is a process by which robot positioning accuracy can be improved. During a manipulator control system design, and periodically in the course of task performing, manipulator geometry calibration is required. Nowadays robot calibration plays an increasingly important role in robot production as well as in robot implementation and operation within computer-integrated manufacturing where the simulated robot must reflect the real robot geometry (Elatta, et al. 2004; Khalil & Dombre, 2004; Perez, et al. 2009).

Computer Vision in Industrial Automation and Mobile Robots

Materials forming, machining and tribology, 2018

Computer vision is presently a very relevant and important tool in both industrial manufacturing and mobile robots. As human vision is the most relevant sense to feed the brain with environmental information for decision making, computer vision is nowadays becoming the main artificial sensor in the domains of industrial quality assurance and trajectory control of mobile robots. Keywords Computer vision Á Industrial automation Á Mobile robots 1 Computer Vision in Industrial Automation 1.1 Artificial Vision in Automation Distributed systems began to be used in the telecommunication sector, pushed by the generalized spread of computers and their need to be interconnected. This context originated the rise of several network topologies. Distributed strategies were rapidly extended to other domains, as they bring several advantages. The distributed strategy has very interesting characteristics as it shares several resources, allowing a more rational distribution among the users. This philosophy presents enormous economical benefits in comparison to traditional centralized systems, where the same resources have to be multiplied. Decentralized management of systems is nowadays an important development tool. This strategy reaches different fields, from agriculture to industry, building automation, etc. [1, 2]. Artificial vision and image processing have already an important role in several technical domains as: (i) pattern recognition, with multiple applications in industrial

Using Robot Skills for Flexible Reprogramming of Pick Operations in Industrial Scenarios

Proceedings of the 9th International Conference on Computer Vision Theory and Applications, 2014

Traditional robots used in manufacturing are very efficient for solving specific tasks that are repeated many times. The robots are, however, difficult to (re-)configure and (re-)program. This can often only be done by expert robotic programmers, computer vision experts, etc., and it requires additionally lots of time. In this paper we present and use a skill based framework for robotic programming. In this framework, we develop a flexible pick skill, that can easily be reprogrammed to solve new specific tasks, even by non-experts. Using the pick skill, a robot can detect rotational symmetric objects on tabletops and pick them up in a user-specified manner. The programming itself is primarily done through kinesthetic teaching. We show that the skill has robustness towards the location and shape of the object to pick, and that objects from a real industrial production line can be handled. Also, preliminary tests indicate that non-expert users can learn to use the skill after only a short introduction. 2 BASIC CONCEPTS AND RELATED WORK The central concepts for the pick skill presented in this paper are robotic skills and object detection. These are covered here.

Integration of a 2D Vision System into a Control of an Industrial Robot

KMUTNB International Journal of Applied Science and Technology, 2014

Industrial robots play an important role in today's production. They are mostly tied to the production process by teached orders. To make industrial robots more flexible and more interesting for the industry, they are often additionally equipped with a vision system. Thus, they are not bound by their fixed program and able to adapt their path to each object individually. This paper explains the cooperation of a six-axis industrial robot and a 2D-Vision System. Here, the precision of the robot and the accuracy of the vision system are combined. The vision system In Sight Micro 1100 acquires quality and localization tasks. It locates the object, inspects it and judged its quality. These results are finally send to the robot controller of KUKA KRC 2 Edition 2005 in the form of coordinates and are ultimately put into action by the industrial robot KUKA KR 16-2. With the software In Sight Explorer 4.8.0 a visual order can be created and adapted to the existing conditions. It offers a variety of preset localizing and qualitative tools. Alternatively, there is the possibility to created special tools in a spreadsheet program. The paper describes the interface between vision system and robot. Finally, an inspection station for work piece quality control is created from the derived results.

Visual Guidance of Robots Integrated in Intelligent Manufacturing

2015

Guidance vision is applied as an advanced motion control method, which provides flexibility when integrating robots in intelligent manufacturing cells with unstructured environment. The paper develops a methodology for on-line implementing vision-based robot control strategies that use robot-object models a priori learned, and are on-line checked for collision-free grasping based on the models of the gripper's fingerprints. Experiments have been carried out on a development platform using a Cobra s850 SCARA robot with compact Adept controller and vision extension.

Vision Based Robot Programming

2008 IEEE International Conference on Networking, Sensing and Control, 2008

Programming of industrial robots is normally carried out via so-called "Teach" or "Offline" programming methodologies. Both methodologies have associated weaknesses like a high time consumption for programming on sculptured surfaces (especially "Teach"), and both methodologies cannot, at the same time, carry information of the real work piece and the ideal work piece (CAD-model). To be able to see both the real and ideal world is especially important when the industrial robot is used in manufacturing processes like machining, grinding, deburring etc. where the difference between the real and ideal world represents the material removal. This paper presents a new vision based programming methodology which combines information of the real and ideal world, especially adapted for robot grinding and deburring operations. Further, the presented methodology is especially developed with simplicity in mind when it comes to manmachine communication. Thus, a standard marker pen can be used by the operator to draw the robot path directly onto the work piece. This line is captured by a vision system and finally leads to the generation of the robot path. The presented methodology is a further development of the previous work of the authors as presented in [1, 21, especially concerning optimization of the robot tool positioning with respect to a work piece surface.

Analysis of the Possibilities of Applying Mobile Robotic Platforms Using Machine Vision in Industry

Periodica Polytechnica Transportation Engineering

The article considers the possibilities of automated use of robotic equipment in order to form an infrastructure for moving goods at enterprises. Areas of application of algorithmic programming languages of object-oriented type in robotics are investigated. The algorithm of operation of a transport vehicle, the movement, which is based on the recognition of the line of motion, describing the route of movement, is presented. The analysis of the peculiarities of the implementation of such problems with the use of OpenCv software library was carried out. The structure of the vehicle is proposed, in particular: its driving mechanisms, control scheme, engines and wheelbase. Further development was made to the algorithms for the management of crawler lorries and the ways of their program realization in various spheres of entrepreneurial activity, where there is a need for the transfer of cargoes in the ordinary areas (construction sites, forest lands, open warehouses, airports, etc.). Bas...

Visual Assistance to an Advanced Mechatronic Platform for Pick and Place Tasks

2010

Recent advances in mechanical and electronic engineering led to the building of more sophisticated mechatronic systems excelling in simplicity, reliability and versatility. On the contrary, the complexity of their parts necessitate integrated control systems along with advanced visual feedback. Generally, a vision system aims at bridging the gap between humans and machines in terms of providing to the latter information about what is perceived visually. This paper shows how the vision system of an advanced mechatronic framework named ACROBOTER is used for the localization of objects. ACROBOTER develops a new locomotion technology that can effectively be utilized in a workplace environment for manipulating small objects simultaneously. Its vision system is based on a multi-camera framework that is responsible for both finding patterns and providing their location in the 3D working space. Moreover, this work presents a novel method for recognizing objects in a scene and providing their spatial information.

A framework of teleoperated and stereo vision guided mobile manipulation for industrial automation

2016 IEEE International Conference on Mechatronics and Automation, 2016

Smart and flexible manufacturing requests the adoption of industrial mobile manipulators in factory. The goal of autonomous mobile manipulation is the execution of complex manipulation tasks in unstructured and dynamic environments. It is significant that a mobile manipulator is able to detect and grasp the object in a fast and accurate manner. In this research, we developed a stereo vision system providing qualified point cloud data of the object. A modified and improved iterative closest point algorithm is applied to recognize the targeted object greatly avoiding the local minimum in template matching. Moreover, a stereo vision guided teleoperation control algorithm using virtual fixtures technology is adopted to enhance robot teaching ability. Combining these two functions, the mobile manipulator is able to learn semi-autonomously and work autonomously. The key components and the system performance are then tested and proved in both simulation and experiments.