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Steve Wardell

How did you come to be part of the machine vision industry?

I have been working at ATS Automation since the day I graduated from university with a Bachelor of Math and Computer Science degree. I am a software programmer at heart, and my first job was developing standard control software in C on a QNX real-time platform for various different pieces of equipment. That equipment included robots, servos, temperature controllers and cameras, among other things. Eventually, we formed a group that concentrated on developing fully automated high accuracy assembly cells. To achieve the levels of accuracy required for these systems, there was a need for tight integration of the motion platforms with high accuracy vision feedback. Given that this was late 80s, early 90s, there weren’t a lot of off-the-shelf machine vision solutions to choose from, so we made our own. That initial work eventually grew into the products and solutions ATS provides today in the machine vision industry. I have held many positions throughout my career here at ATS, most recently, director of the company’s imaging group for the last five years.

What role does North America have in the development of machine vision?

After having the privilege to sit on the board of the AIA for the last few years, I’ve come to realise that the North American machine vision industry is a diverse group of entrepreneurial and highly productive companies. These companies, along with various different relationships to educational and research institutions, are continuing to push the boundaries on where machine vision solutions can be applied. However, where those applications and developments arise tend to be more global in nature. Being responsible for the machine vision solutions of one of the largest automation providers in the world, I have the opportunity to see application needs from around the globe daily. It amazes me how the solutions that this industry offers can be applied to so many different areas, often in the same manner, regardless of region. As a result, harmonisation and standardisation within the industry can only benefit both the equipment manufacturers and the integrators. I see North America taking a leading role in working towards a more standardised industry worldwide.

What do you see as the major growth sectors?

As sensors get smarter, the ability for end users to deploy some form of machine vision solution into their business becomes less costly and more reliable. The need for specialists remains, but the challenges they are trying to solve get more complicated as the bottom end applications become commonplace and more do-it-yourself. As such, I see a large growth sector within the industry for these smart sensors to be used for more and more data-gathering purposes – not necessarily to give functional feedback, but rather to collect and monitor systems by providing information easily and inexpensively. That data eventually ties into the big data repositories, which firms are all trying to figure out how to exploit. Machine learning techniques are now making the transition from university labs into practical application space, and companies able to supply means of collecting big data and then processing it for useful feedback are sitting in good positions for growth.

What are the important technological challenges facing the industry?

I began to allude to one of the main challenges above. We have seen great strides in the capabilities of cameras and systems to produce more and more image information depth at speeds that just can’t be kept up with currently. However, just like the regular dance that computer hardware and software advancements take, a similar dance will still be happening within our industry. Just when you think there is no way for us ever to be able to handle all the pixels that are being thrown at us now, algorithms and methods appear to gobble them up and require even more. It’ll then be back to the hardware folks to see what they can offer up next. I see us currently at the point where the hardware advancements are outpacing the software within the industry. Approaches like deep learning over traditional image processing will emerge to fill in the gap.

What will be the most significant commercial change in the industry in the coming years?

I believe machine vision will begin to step out of industry and become more mainstream in the consumer world. Everyone now carries around a camera with them all the time. Applications are being churned out regularly to make more and more use of these camera images in cool and creative ways for the benefit of those consumers. The lessons and approaches learned over the last 30 to 40 years in the machine vision world are being applied mainstream in everyday culture. Things like optical character recognition were leading-edge technology within our industry only a short time ago. Now, a phone does it in real-time to translate foreign signs so you can get around more easily in a country where you don’t speak the language. How the machine vision industry adjusts now to aligning developments from both the industrial and the commercial worlds within this space will dictate how it sets itself up for the future. 


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