Personal robots are expected to enter our homes and daily lives in the coming decades. They will be active in helping people physically, socially and/or cognitively. They will become an integral part of our lives. Especially for those with physical or cognitive disabilities. These robots will allow the elderly or the disabled to live more comfortably and independently.
There is a dramatic paradigm shift in industrial robotics. Autonomous robots are getting closer to people in factories. We may see a shift to robots that are intuitively and dynamically reprogrammed by workers. They collaborate with them to achieve production and service issues.
Robots work alongside humans in various workplaces. We could see an army of these robots working in factories, warehouses, retail stores, and even hospitals. As they evolve, we need to make it easier for people to trust robots and for robots to understand human cues.
However, robots will become quite common around us. They will operate in uncontrolled environments and interact with non-expert users. We as a society must address these pressing issues.
This is a primary issue that needs to be addressed. Understanding human behavior is one of these problems. Robots need to understand human behavior at different levels of abstraction. This is very necessary to function in a useful, appropriate and acceptable manner.
This is especially true when autonomous mobile robots (AMRs) are involved. These dynamic robots are, as the name suggests, autonomous. They don’t need a traditional human-machine interface to control them.
An AMR is programmed to perform a specific task and then dispatched to complete it. It works as one goes through a standard download process before it works on its own.
AMRs and humans are free to operate without much control. They need to figure out how to communicate with each other. We need to teach them both appropriate social behavior.
AMRs must understand and monitor the social behavior of their employees. This is quite important to maximize their effectiveness. It will also in turn increase human-robot cooperation, reducing the risk of accidents.
Cloud-based deep learning learning technologies are critical to making this happen.
A different point of view
Some people may be concerned about teaching robots to behave like humans. But they need to communicate more effectively with each other. Their success will ensure that workflows run smoothly in a fast-paced environment. It is very important where there are high stakes supply chain operations.
Everyone needs to get along if you want to deliver what customers need, when they need it. It is appropriate to demonstrate to workers that AMRs understand when to engage and when to keep their distance. AMRs should be trained on what is acceptable and what is not.
But before we can do that, we need to ensure that AMRs can see, understand and respond to their surroundings. They cannot exist in their own world, as many robots do today, seeing only “myself”, “obstacle” or “free space”.
Similarly, human workers need to be able to see what is happening around them from a different perspective. They must be able to grasp the scope and depth of the world around them. The human workforce must be aware of the intelligence and capabilities of AMRs.
We can expect people to be fearful, hesitant and unsure of themselves around AMRs. Unless we change how robots and humans think and react to each other. They will continue to believe that the robot is too aggressive or that it is ignoring them.
As a result, your AMRs will not be used and you will have to wait longer to see your return on investment (ROI). Some 83% of warehouse workers say AMRs have increased their productivity and reduced travel time. It’s a win-win situation for you and your frontline teams.
Cloud is a force multiplier (training)
Earlier we told robots what to do. Give them operating parameters and let them do the job to the best of their ability.
We can now enable AMRs to adapt to their surroundings. Machine learning and convolutional neural network technologies are behind them.
They can detect and distinguish different semantic objects. This includes people, trucks and pallets to make appropriate behavioral decisions. These decisions are based on coded behavior as well as current sensory data.
These AMRs do not act only on the basis of implied guidance; they act in reality. In other words, the cloud makes it possible to code AMRs with social behavior. Companies must haveea stable Internet connection to ensure that there are no interruptions in the work process. A good internet connection is essentialthe pillar of the whole structure. They are necessary to make people feel at ease working with them.
As a result, it becomes easier to teach people the social behaviors needed when working with robots. People will be able to see AMRs navigating or leaving someone who shouldn’t be in their bubble.
They will also see how AMRs can safely enter their premises and assist them if necessary.
Human behavior towards robots will change when they are trusted not to lie. Once they are equipped with appropriate social behavior. Reluctance to engage with AMR will decrease as confidence in the robot’s “behavior” increases.
People will begin to recognize and appreciate the benefits of AMR, and adoption rates will increase. 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 cloud and a safe and high speed internet connectionAMR:They could not work independently or cooperatively as they do now.
The cloud is driving robotics. It’s a force multiplier, at least when it comes to teaching intelligent robots social behavior. It is vital ammunition to convince people that AMRs are friendly.