Personal robots are expected to enter our homes and everyday life in the coming decades. They will be an asset in assisting humans physically, socially, and/ or cognitively. They will become an integral part of our lives. Especially for the ones with physical or cognitive disabilities. These robots will allow the elderly or handicapped to live more comfortably and independently.
There is a drastic paradigm shift in industrial robotics. Autonomous robots are becoming closer to humans in the factories. We can see a shift towards robots that are intuitively and dynamically reprogrammable by the workers. They are working collaboratively with them to achieve manufacturing and maintenance tasks.
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The Robot Workforce
Robots are working alongside humans in a variety of workplaces. We can see an army of these robots working in factories, warehouses, retail stores, and even hospitals. As they progress, we must make it easier for people to trust robots and for robots to pick up on human cues.
Nonetheless, robots will become quite common around us. They will be operating in uncontrolled environments and interacting with non-expert users. We, as a society, will need to address these pressing issues.
This is a prime issue that will need to be addressed. Understanding human behavior is one of these issues. Robots will need to understand human behavior at various levels of abstraction. This is very much needed to act in a useful, relevant, and acceptable manner.
This is especially true when autonomous mobile robots (AMRs) are involved. These dynamic robots are, as the name implies, autonomous. They do not need a traditional human-machine interface to control them.
The AMR is programmed to perform a specific task and then sent off to complete it. It works like how a human goes through a standard onboarding process before working on their own.
AMRs and humans are free to operate without much oversight. They must understand how to interact with one another. We need to teach them both appropriate social behaviors.
AMRs must understand and take cues from their human coworkers’ social behavior. This is quite important to maximize their effectiveness. It will also in turn increase human-robot collaboration, reducing the risk of mishaps.
Cloud-based deep learning training technologies are critical to making this happen.
A Different Point of View
Some people may be concerned about teaching robots to behave more like humans. But they must interact with each other more effectively. Their success will ensure that workflows run smoothly in a fast-paced environment. It is highly crucial where there are high-stakes supply chain operations.
Everyone must be able to get along if you are to deliver what customers need when they need it. It is pertinent to show the workers that AMRs understand when to engage and when to keep their distance. AMRs need to be trained on what is and are not acceptable.
But, before we can do that, we must ensure that AMRs can see, understand, and respond to their surroundings. They cannot exist in their world, as many robots do today, only seeing “myself,” “obstacle,” or “free space.”
Likewise, human workers must be able to see what is going on around them from a different angle. They must be able to comprehend the scope and depth of the world around them. The human workforce should be aware of the intelligence and capabilities of AMRs.
We can expect people to be intimidated, hesitant, and unsure of themselves around AMRs. Unless we change how robots and humans think and react to one another. They will continue to believe that a robot is being too aggressive, or that it is ignoring them.
As a result, your AMRs will be underutilized, and you will have to wait longer to see a return on investment (ROI). Approximately 83% of warehouse associates say the AMRs have increased their productivity and reduced travel time. It is a win-win situation for you and your front-line teams.
The Cloud Is a Force Multiplier in (Training)
Earlier, we used to tell robots what they needed to do. Give them operating parameters and have them perform the work according to their capabilities.
We can now give AMRs the ability to adapt to their surroundings. Machine learning and convolutional neural net technologies are the ones behind them.
They can detect and distinguish between different semantic objects. This includes people, forklifts, and pallets to make appropriate behavioral decisions. These decisions are based on encoded behaviors as well as current sensory inputs.
These AMRs do not operate only on inferred guidance; they operate in reality. In other words, the cloud enables encoding AMRs with social behaviors. Companies need to have a stable internet connection to ensure there is no interruption in the workflow. A good internet connection is an important pillar of the entire structure. These are needed to make humans feel at ease working alongside them.
As a result, teaching people the social behaviors required when working with robots becomes easier. People will be able to see how AMRs navigate around – or away from – someone who should not be in their bubble.
They will also see how AMRs can enter their space safely and assist them when needed.
Human behavior towards robots will change once they can be trusted not to go rogue. Once they are equipped with the appropriate social behaviors. The hesitation to engage an AMR will diminish as trust in the robot’s “demeanor” grows.
People will begin to recognize and value the benefits of AMRs, and adoption rates will rise. As a result, businesses will be able to expand their use of robotics automation with little resistance.
So, the next time someone tells you that the cloud isn’t doing much for robotics automation, remind them how important it is. Without the cloud and a secure and high-speed internet connection, AMRs couldn’t work autonomously – or collaboratively – the way they do now.
The cloud is propelling robotics forward. It is a force multiplier, at least when it comes to teaching intelligent robots social behavior. It is a vital ammunition for convincing people that AMRs are friendly.