The human-robot relationship is a complicated one. Depictions of robots in science fiction and other mainstream media leave us thinking these complex machines are a 1:1 replacement for humans (or depending on the movie, one robot’s super-human capabilities replace numerous people). Because of this, it’s tempting to assume that robots can be dropped into any workflow and automate every problem that arises.
However, anyone who’s worked in an industrial environment knows that things rarely go exactly as planned, and exceptions are the rule more often than not. Dealing with the unexpected is where humans shine and is the reason why there will always be a place for humans in industry.
Yet, robots do play a critical role. Mobile robots, specifically, have been shown to increase throughput up to 30% and reduce value-added travel by up to 50% in large industrial facilities. They are best used for long-haul applications like staging lanes to end of rack put-away, or milk runs in manufacturing or sortation hubs.
It’s important to know where robots fit, and how they fit. This article will unpack three of the biggest misconceptions about industrial automation.
1: Robots can solve problems on their own
From facilities management and manufacturing to warehousing and beyond, we’ve seen a drastic increase in automation across nearly every industry. In fact, McKinsey estimates 88% of businesses worldwide plan to adopt some type of robotic automation into their infrastructure. While large-scale adoption can positively impact business gains, it will not replace human intelligence.
Tesla CEO Elon Musk once tweeted, “Yes, excessive automation at Tesla was a mistake. To be precise, my mistake. Humans are underrated.” Elon’s quote exemplifies that while robots can help streamline repetitive and often dirty and dangerous tasks humans traditionally performed, they can’t replace them. Humans are needed to troubleshoot edge cases with problem solving and creativity – something robots lack.
The relationship enables workers to do what makes us uniquely human while eliminating the mundane tasks that can hamper employee morale. In fact, automation can even create the opportunity for many new job categories we haven’t even considered yet given the increase in productivity they can achieve. Think about the number of people currently employed in programming computers, an industry that barely existed a few decades ago. For robots and humans, work is better together.
Yes, excessive automation at Tesla was a mistake. To be precise, my mistake. Humans are underrated.
— Elon Musk (@elonmusk) April 13, 2018
2: Robots have cognitive reasoning
Science fiction would have us believe that robots get smarter with time. To watch autonomous mobile robots (AMRs) navigate, you could easily jump to that conclusion: a self-driving pallet truck is driving forward, for instance, but a box falls or a human approaches and the truck stops or maybe navigates around the obstacle. And we love to attribute human levels of understanding to these actions.
In reality, robot “learning” and human learning are completely different. Robots can really only learn things that they were programmed to learn. For example, a robot may “learn” the best path to take over time because it records the time it takes to travel different paths and then uses that data to pick the best route for the next trip, much like your GPS in your car.
So broadly speaking, robots “learn” by collecting more data and then applying algorithms to that data that the programmer thinks will help it perform better in the future. But a robot won’t spontaneously start learning things it is not programmed to learn. It may be more accurate to say robots “optimize performance based on data” rather than “learn.”
Some call this artificial intelligence or AI. AI delivers the ability to collect data and uncover patterns that can be used to enhance performance over time. This data can come from sensors, real-time performance and even interactions with human coworkers. When processed through an AI-powered continuous learning engine, like Vecna Robotics’ Pivotal platform, robot performance will improve overtime as it collects data about its work environment and uses that data to optimize future work.
For example, suppose each time the robot makes a delivery to a certain area on Friday it takes longer than normal because of a large order that comes in each week. In that case, the system may decide to schedule that delivery for a different time to avoid that congestion.
3: Robots can collaborate
Some of us might remember when it was unheard of for a mainframe computer to run software written by a different company than the one that built the hardware, or even for a cell phone to run an application written by someone that didn’t work for the cell phone manufacturer. But without today’s level of interoperability where different companies’ technologies work together seamlessly, we wouldn’t have achieved most of the benefits that computers and mobile devices have created for us. This expectation has carried over to the robotics industry too. Here interoperability is a work in progress, but not yet a reality.
Today, most robots do not communicate with other robots from different vendors, and generally do not run software written by others. However, this spring, MassRobotics announced its interoperability standards. While they haven’t yet been widely adopted, many organizations are taking steps to make their robots “interoperability-enabled” so they can work alongside platforms from other vendors. Once they’re adopted and combined with effective orchestration, they will unlock effective collaboration and unleash true productivity.
With a system-wide view, orchestration engines can deploy the right resource to the right place at the right time. Those resources might be human workers, manual equipment, robots, or other systems. The orchestration engine can consider all automated systems within the environment from multiple makers. The orchestration engine knows which people or systems are available to work, what type of work each are good at, what jobs need to be completed, and how to assign each task to ensure work is completed most efficiently.
When we look at warehouses, for instance, we see a continually moving ecosystem. From shipments coming in to products going out, logistics can be challenging to manage. So, what happens if an exception occurs like a late delivery? Often, the people and machines would unproductively wait, but superior orchestration would instead repurpose the resources for other tasks and brings them back once the shipment arrives, so neither humans nor the robot wastes time waiting.
Robots aren’t here to take over. When used correctly, they’re empowering humans to live more productive and fulfilling lives by allowing them to take on the more interesting jobs and simultaneously propel the industry forward through superior productivity. Whether you’re in charge of managing a warehouse, airport, distribution center, office park, or any other facility, automation can help you and your employees get more work done. Looking towards the future, businesses that ensure they’re using AI to orchestrate and optimize workflows between humans, machines and robots will be the real winners.
About the Author
Daniel Theobald is the chief innovation officer and founder of Vecna Robotics, the autonomous mobile robot and workflow orchestration company. Theobald has decades of experience leading research scientists and teams of engineers in developing cutting-edge technology. He has 67 issued patents and more than 30 patents pending.
Theobald has also been on the forefront of robotics for more than 20 years, working closely with DARPA, DOD, NASA, NIH, USDA and many others to advance the use of robots and AI software to improve warehouse automation. In addition to founding Vecna Robotics, he also co-founded Mass Robotics, a non-profit dedicated to the global advancement of the robotics industry. Daniel is dedicated to the idea that technology can be used to empower people worldwide to live more fulfilling lives.