Robotic Eye Sight Key To Boosting Engineering Job Recruiting

Robotic eye sight will result in more engineering recruiting because it is a major new frontier in robotics, bionics and automation. Future breakthroughs in autonomous vehicles that can navigate obstacles, humanoid robots that can more closely integrate with humans and drones will mean the need for more and better software, hardware, bionic, biomechanics engineers.
Robotic eye sight is the major new frontier in robotics, bionics and automation. It is the cornerstone of future breakthroughs such as autonomous vehicles that can navigate obstacles, humanoid robots that can more closely integrate with humans and drones that can fly more safely.

Food manufacturers are already combining advances in laser vision with artificial intelligence or AI software. This technology allows automated arms to carry out more complex tasks. Slicing chicken cutlets precisely or inspecting toppings on machine-made pizzas are but two examples of complicated tasks already being assigned to robotic machines.

Other companies such as logistic and consumer electronics companies are effectively making use of the technology as well.

However, solving the next, more difficult and challenging levels is the key to further advances. This will include robotic viewing from multiple angles, bionic vision combining with data analysis for decision making, more advanced self-driving cars, humanoid robots, autonomous drones and even 3-D imaging.

Because companies worldwide are investing heavily in computer vision-based technology, engineer job demand will increasingly outstrip engineering candidate supply. For example, the sensing and imaging market will grow about 10-fold to $18.5 billion by 2023, market-research firm Yole Développement forecasts.

The demand for engineers is far outpacing the present and future supply. As a result, more software, hardware and biomechanics experts are needed to develop revolutionary robot sight algorithms.

Manufacturing Companies On Robot Recruiting Forefront

Food manufacturers have been early adopters of new technologies including vision automation. This technology has been used for many years for tasks such as reading bar codes and sorting packaged products. Leaders now are finding the technology valuable because robot eyes outpace the human eye at certain tasks.

For years, Tyson Foods Inc. used sensors to map chicken fillets. The chicken can be cut to the precise specifications required by restaurant customers who need them to cook uniformly. However, exposure to the high pressure, high temperature water requirements kept causing equipment failures.

Now technical improvements, tougher materials and declining prices mean the company can integrate vision technology in their facilities. This includes the new $300 million chicken-processing plant in Humboldt, TN, said Doug Foreman, who works in technology development at the Springdale, AR-based food company. The technology could help optimize the use of each part of the bird, he added.

Tyson is investing in a manufacturing automation center to further explore the application of vision technology in their operations, the company said.

You can do more with a robot that can see,” said John Keating, a senior director at Natick, MA.-based Cognex Corp., which makes vision sensors used by global manufacturers, including food processors. Vision-sensing devices can be used all through the sausage-making process, from measuring to inspecting for defects to quality control on the final product, Mr. Hosler said.

Advances so far allow vision technology to ensure frozen pizzas have the correct toppings. Other applications include the ultrasonic slicing of cheese, cutting bread rolls with water jets and picking pancakes off a production line.

Logistics companies deploy robotic vision to more quickly identify packages. Consumer electronics companies help position liquid-crystal display screens more precisely than is possible with the naked eye.

Data May Aid Robotic Sight To View From Multiple Angles

While vision sensors are good at scanning images for what’s missing, robotic eyes face a wall in inspecting objects from multiple angles, according to engineers at Kyoto, Japan-based Omron Corp. Their proposed solution: big data.

To teach a sensor to distinguish a chocolate chip from a burned bit in a cookie, for example, Omrom is using AI to analyze thousands of inspection results. That sort of software will be crucial as robots increasingly permeate the economy.

The Challenges Of Self Driving Cars Is Far More Complex

The difficulties solving technical challenges on food assembly lines and other applications shows how hard it could be to develop robotic vision for more complex tasks. Self driving cars where human lives are at stake demand precision.

Car makers are historically the biggest user of vision technology. They are currently using it for emergency braking, scanning road signs and even avoiding doors opening into approaching vehicles. However, a self-driving car needs to see from multiple angles and make split-second calculations to avoid one obstacle, or human being, without hitting another.

Even Further Challenges Present Themselves

The next big thing in bionic machine vision is 3-D imaging—technology that can measure depth as well as diameter and gaps. One application is in bin picking. A robot able to sift through a box of items and identify, organize and adjust the contents could eventually step in for human workers in shops and warehouses.

The high cost of such technologies are a barrier to them being implemented for such tasks, said Jairam Nathan, analyst at Daiwa Capital Markets. “3-D vision increases the capability of robots significantly in tasks like bin picking, but the systems are still expensive,” he said.

Recruitment Complications In A Tight Job Market

The overall number of available jobs in the U.S. exceeded the number of job seekers by more than 650,000 in July. This is a gap that has been growing. It is a sign of an increasingly tight labor market that is altering how employers find workers.

The number of available jobs in the U.S. rose by about 117,000 to a seasonally adjusted 6.94 million in July, the Labor Department reported recently. That is the highest level on record back to 2000, exceeding the prior peak set in April. The figure also exceeds the 6.28 million Americans who were unemployed during the month, meaning they were without work but actively seeking a job.

The tight labor market, shown by an unemployment rate holding near a 17-year low, is shifting more power to workers. Increasingly workers are willing to quit their jobs knowing they can find higher paying positions elsewhere. In July, 3.58 million workers voluntarily left their jobs, the highest level on record according to the Labor Department.

Further challenges remain in coaching robots to understand what they are seeing. This is why talented engineers in a wide range of fields will be needed to solve these key engineering problems.

Our recruiters at Strategic Search Corporation have increasingly found over the last 18 months the supply of skilled engineers is very limited and the demand for labor is expanding. As a result, we have developed 12 Commandments Of Recruiting to help our recruitment clients more seamlessly navigate this tight job market.

Learn more about the 12 Commandments of Recruiting or contact us today at 312-944-4000 to discuss your engineering recruitment needs in Robotic and Bionic Eye Sight or other leading technology field such as Artificial Intelligence (AI), Virtual Reality (VR) or Internet of Things (IoT).
Engineering, technical, R&D recruiting experts

6 Responses

  1. Well stated, Scott. Drones are also on the forefront as such per being a likely automated first line of sight in gathering data to distribute across real-time visual management (VM) and or supervisory control and data acquisition (SCADA) systems. Komatsu’s operations are a keen example as their automated drone flights catalyze automated robotic construction operations on a daily/global basis by way VM system controls revolving around Skycatch software.


  2. Robert,
    I greatly appreciate your insights on my article on the state of robotic vision and how it is impacting robot recruiting. Additionally, your thoughts on automation engineering are very interesting.

    Thanks for sharing,


  3. Scottt,

    Great article, advances in computer vision open up lots of tasks to automation. At iRobot we use computer vision to help Roomba navigate and now to map homes. This will allow them to get smarter with time as they understand their surrounds better. The fusion of big data with computer vision creates tremendous opportunities for better insights and functionality in a large range of applications. Many of the biggest advances in AI are coming in the computer vision feild, leading to even more advances such as in the medical field.

  4. Christopher,
    I greatly appreciate your comments on my recent article on how robotic sight improvements will drive more robot engineering job recruiting and how it will effect automation as well.

    Thanks again for sharing,


  5. Computer vision technology has been implemented greatly in manufacturing automation to reduce the repetitive labor. The traditional assembly line can be simplified further with the integration of computer vision to robotic arm, that was only used to pick up the parts in certain orientation. Now, the robot can adjust itself to the orientation of the complex parts. It is amazing when you see it in person. i would expect that the growth in this field in the next couple of years would definitely demands more skilled engineers to this field as many universities have set up a dedicated concentration for computer vision for their engineering programs.

  6. Kyle,
    It is great to hear from you again. I greatly appreciate your comments on my recent article on how robotic sight is improving robot engineering recruiting.

    Thanks again,


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