UKIVA Machine Vision Conference and Exhibition

The show will take place on 6 June at the Marshall Arena in Milton Keynes.

The organisers told MVPro Magazine that the event is becoming increasingly popular with attendance figures in 2018 up 17% compared to 2017.

The 2019 iteration will follow a similar format to previous years, with a programme of technical seminars supported by an exhibition featuring vision component manufacturers, vision component and system distributors and systems integrators from around the world.

The 2019 Conference will feature an additional theme, covering applications of vision in automation and robotics.

Chris Valdes, UKIVA event organiser and business development manager for the PPMA (Processing & Packaging Machinery Association), said: “At the event in 2018, a number of exhibitors included robots and cobots in their displays, which provided a great deal of interest. There have also been recent developments in the communication standards for machine vision and robots for use in Industry 4.0, making technical seminars on vision, robotics and automation even more relevant.

“UKIVA has a natural affinity with the combined use of vision and robotics as BARA (British Automation & Robotics Association) is, like UKIVA, part of the umbrella PPMA (Processing & Packaging Machinery Association) and many of our members have an active interest in BARA as well.”

The Machine Vision Conference program features around 60 technical seminars across eight different subject areas: Vision in Robotics, Understanding Vision Technology, Deep Learning & Embedded Vision, 3D Vision, Optics & Illumination, Camera Technology, Systems & Applications and Vision Innovation.

The programme has been designed to provide interesting content ranging from ‘understanding vision technology’ to ‘vision innovation’. It accommodates visitors with any level of vision knowledge and experience, from those new to the subject to experts. A number of the presentations will include examples of the practical use of vision systems across a wide range of industries. Visitors are free to attend whichever talks are of the most interest and presenters will be on hand throughout the day for further discussions, providing delegates with outstanding opportunities to talk to people with experience of delivering real world vision solutions.

The Conference will include a focus on vision and robotics, showing how this powerful combination can improve productivity and make a significant contribution as part of Industry 4.0 and smart factories. This will feature a contribution from BARA (British Automation and Robot Association), who will also be demonstrating a working robot cell.

The Conference also provides delegates with the opportunity to explore the latest developments in core vision subjects such as camera technology and illumination and optics. There are sessions on the highly popular 3D imaging technology and newer topics such as deep learning and embedded vision as well as a thread devoted to vision systems and applications.

Dr Luca Benedetti from Kudan has been named as the first keynote speaker for the UKIVA Machine Vision Conference and Exhibition.

Dr Benedetti will deliver a keynote address entitled: ‘Visual SLAM in the Wild.’

With Simultaneous Localisation and Mapping (SLAM) gaining traction in the world of industrial vision, Dr Benedetti will describe the real-world challenges of deploying a SLAM system across a variety of applications as well as designing a SLAM system that’s versatile both in terms of hardware and software.

UKIVA Chairman Allan Anderson said: “We are delighted that Dr Benedetti has agreed to speak at the Conference. Kudan is accelerating the evolution of virtuality (AR/MR/ VR) and Robotics (automobile/drone/robot) by developing computer software algorithms classified as Artificial Perception (AP). They are pioneers in this field. With the combination of AP and AI, machines are getting closer to sensing and interacting with the world like humans do, utilising both eyes and brain.”

SLAM refers to the process of determining the position and orientation (localisation) of a sensor with respect to its surroundings, as well as simultaneously building a map of the surrounding environment. Most modern SLAM systems used today are based on vision, as they use one or more cameras as the main sensing device and visual SLAM is quickly becoming an important advancement in embedded vision with many potential applications.

SICK plans to use the 2019 UKIVA Show in Milton Keynes to show how machine vision is being demystified for a growing number of adopters, backed by greater accessibility to ‘all-in-one’ intelligent vision sensors powered by ready-made software applications.

Recently appointed as vice-chairman of UKIVA, SICK’s Neil Sandhu will deliver two presentations to delegates that put the case for removing the complexity that can surround implementing a vision solution, empowering users to set up vision systems, including more difficult 3D applications, with ease.

“Machine vision has been a headache too far for many engineers looking to improve their production or materials handling processes with better standards of inspection. Programming a reliable system to process the data from a vision camera has been feared in the past as something of a black art,” said Sandhu who is SICK’s UK Product Manager for Imaging, Measurement & Ranging.

“But now rapid advancements in camera technology combined with intelligent on-board processing capability have brought high-performance applications within the reach of many production teams who would previously have felt excluded from them. So, the time has come to present a more accessible and democratised outlook for vision in future and to encourage more users to enjoy the benefits.”

SICK’s technology demonstrations at the Show will underline the company’s ambition for intelligent devices like the Inspector P 2D and the Trispector 1000 3D smart vision sensors to work in a similar way to smartphones powering ready-made applications that are easy to set up and use, selected via a central cloud-based repository of industry solutions.

Central to this vision is SICK’s AppSpace platform for development and pooling of software applications, for which a growing number of solutions are now being released both by SICK and by its automation partners.

On show at UKIVA will be the new 4Sight Automated Print Inspection System developed in SICK AppSpace with packaging automation specialists Autocoding Systems. The breakthrough of 4Sight is that it communicates directly with common printer types, such as inject and laser thermal transfer. It can therefore automatically recognise and inspect the alphanumeric code applied by the printer and seamlessly continue the inspection whenever a code is updated, for example with a new date or batch number.

There is no requirement to “teach” the camera what to look for, or for fixturing using an edges or logos. Highresolution, high-reliability and high-speed image processing are assured by hosting the solution on the SICK Inspector P vision sensor.

SICK will also demonstrate its entry-level robot guidance solutions using smart 2D and 3D vision sensors. The Inspector PIM60 URCap integrates SICK’s Inspector PIM60 2D vision sensors with Universal Robots. Simple to set up and use, the combination delivers a powerful toolkit for creating a vision-guided robot task with minimum time and effort. Configuration is achieved in minutes through the UR controller or the SICK Inspector PIM60 without need for an additional PC.

SICK’s Trispector P Beltpick is a 3D vision guidance solution for robot picking with improved z-axis control, enabling gentle handling of complex shapes and profiles, or picking products with variable heights from a conveyor, for example. The system adapts the robot’s picking action to the height of each individual product, reducing the risk of damage. With ‘plug-and-play’ support for ABB, Staubli and Universal Robots, users have access to a range of SICK AppSpace apps for belt picking applications. Other robot manufacturers can also be integrated with the new system.