Artificial Intelligence and Robotics

Physical robots have been around for almost a hundred years, but not without their limitations. In the 1990s the idea of the collaborative robot, or cobot, emerged to help find ways to put robots in closer proximity to humans, but it is only through the inclusion of AI that robotics can continue to progress. 

                                           

While the term robotics conjures up visions of hardware machines performing a wide range of tasks, the term robot is now used to describe any sort of software or hardware-based automation that can perform a task.

However, many of these software robotics systems are limited in their ability and are not able to communicate with other systems or robots to carry out these tasks. With the addition of machine learning, robots and cobots can improve their communication and handle even more complex tasks without the normal risk associated with simpler bots.

Cabot's and software:-

Cabot's are physical robots that are intentionally designed to operate in close quarters with humans. They are finding increasing use in a variety of different settings, performing pick-and-pack warehouse activities, delivery of goods, and a variety of assistive roles. Increasingly, we are seeing cobots in places as diverse as retail stores, museums, hotels, hospitals and even inside homes.

In this context, robotic process automation (RPA) refers to those software automations that perform repetitive user interface-based tasks that would otherwise be performed by a human, such as typing, clicking, swiping, copying and pasting, and a range of UI-based interactions.

But, if a form layout changes, or additional fields of information are required, these bots are not able to process and handle these exceptions and changes, causing them to fail and making them very brittle.

How AI and machine learning are working with robotics

What makes a robot powerful is an ability to think on its own. This is where artificial intelligence and robotics can come together. Companies are increasingly looking for robots to move past automation and tackle more complex and high-level tasks.

AI can help a robot do a lot of tasks, from successfully navigating their surroundings, to identifying objects around the robot or assisting humans with various tasks such as bricklaying, installing drywall or robotic-assisted surgeries.

Robots can benefit from AI and machine learning in different ways, and these AI-enabled capabilities include:

• Computer vision. AI and computer vision technologies can help robots to identify and recognize objects they encounter, help pick out details in objects and help with navigation and avoidance.
• AI-enabled manipulation and grasping. Long considered a difficult task for robots, AI is being used to help robots with grasping items. With the help of AI, a robot can reach out and grasp an object without the need for a human controller.
• AI-enhanced navigation and motion control. Through enhanced machine learning capabilities, robots gain increased autonomy, reducing the need for humans to plan and manage navigation paths and process flows. Machine learning and AI help a robot analyze its surroundings and help guide its movement, which enables the robot to avoid obstacles, or in the case of software processes, automatically maneuver around process exceptions or flow bottlenecks.
• Real-world perception and natural language processing. For robots to have some level of autonomy, they often need to be able to understand the world around them. That understanding comes from AI-enabled recognition and natural language processing. Machine learning has shown significant ability to help machines understand data and identify patterns so that it can act as needed.

In the past, researchers have long thought about how to apply artificial intelligence to robotics but ran into limitations of computational power, data constraints and funding. Many of those limitations are no longer in place, and as such, we now may be entering a golden age of robotics. With the help of machine learning, robots are becoming more responsive, more collaborative, and integrated into other systems.

Likewise, many of the RPA vendors are adding intelligent process automation to their bots to help increase their usefulness. As such, they are looking at AI technologies such as NLP or computer vision to help make these bots more intelligent. Bots that leverage machine learning and adapt to new information and data can be considered intelligent tools that can significantly impact and increase the tasks performed rather than just bots.

Growth of robotics:-

The use of robots in many industries is becoming increasingly common. These robots can either be physical robots or software bots. It is estimated that there will be 3 million industrial robots in operation during 2020. Furthermore, Gartner projected that RPA software spending was over $1.3 billion in 2019. As such, the need and desire for bots of all sorts is seemingly only to going to increase.

Examples of AI powered robotics include: robotic surgery tools that are able to assist surgeons, law enforcement bomb robots that are able to navigate into dangerous terrain to minimize human injury and casualty, and food and package sorting robots that are able to sense different materials and properly pick and sort the objects.

With the use cases seemingly limitless and cutting across many sectors, there is much innovation still to be had and the robotics industry isn't going away anytime soon. Many companies are finding increasing value, efficiency and accuracy from bringing robots into their various operations. This stems from the proof of ROI in the industry and, as people continue to feel more comfortable working with robots, companies will continue to invest in the technology. The addition of artificial intelligence into robotics its making them more useful than ever before.

IROBOT: SMARTER HOME ROBOTS

Industry: Consumer Electronics, Software, Hardware

Location: Bedford, Mass.

 

HANSON ROBOTICS: BUILDING HUMANOID ROBOTS

Industry: Robotics, Artificial Intelligence

Location: Hong Kong

EMOTECH: OLLY, AN AI-ASSISTANT WITH PERSONALITY

Industry: Robotics, AI, Hardware

Location: London

Application of Sensors in Robotics

The sensor helps the robots to sense the surroundings or perceive the visuals of the environment. Just like five key sensors of human beings, combinations of various sensing technologies are used in the robotics.

From motion sensors to computer vision for object detection, there are multiple sensors providing a sensing technology into changing and uncontrolled environments making the AI possible in the robotics.

Uses of Types of Sensors in Robotics:

• Time-of-flight  Optical Sensors
• Temperature and Humidity Sensors
• Ultrasonic Sensors
• Vibration Sensors
• Millimeter-wave Sensors     

What can be sensed by the robots by the help of sensors

• Direction, light
• Sound, frequency
• Temperature
• Object proximity: the presence of the object and the distance can be determined
• Physical orientation and position
• Magnetic and electric fields
• Resistance

What are the required features of sensors

• Accuracy
• Operation range
• Quick response
• Calibration
• Reliability
• Cost and ease of operation

What is an end effector in robotics

An end effector is a device at the end of the robotic arm, which is designed to interact with the environment. Mostly end effector consists of gripper and tools.

What are the different types of sensors used in industrial robots

There are two categories of sensors used in industrial robots they are internal and external. Internal type is used to control the position and velocity of the manipulator’s joints while the external is used to coordinate the operation of the robot with the other equipment.

Commonly used sensors in robotics

Position sensors

Position sensors can monitors the location of the joints and give the information to the controller by this the robot can determine the position of the end effector, the end effector is a part of the robot

Range sensors

These sensors can measure the distance between a point in the robot and the point that surrounds the robots. This is mostly done with the help of cameras. These sensors are used in end effector to calculate the distance between the sensor and the work part. Types of range sensors are sonar, laser range finder, structured light, etc, large distance can be measured by this sensor.

Heading sensor

Heading sensors are sensors that can determine the robot’s orientation and inclination with the given reference.

Velocity sensors

The speed of an object could be known with the help of this sensor. Due to the effects caused by the mechanical force, gravity, etc, the desired speed and required force to reach the speed can be computed.

Vision sensor

To pick certain devices vision sensors will be useful, robots can handle workpiece which is randomly piled by using a 3D vision sensor

Force sensor

Parts fitting and insertion can be done by the help of this sensor robots can do precise fitting and insertion of machine parts with the help of the force sensor. A robot can insert parts that have the phases after matching their phases in addition to simply inserting them

Proximity sensors

This sensor can detect the presence of an object within a specified distance. Many sensors give feedback to the robot if it is near an object or obstruction and this can be done by a contacting or by non-contacting methods and this type of sensors is called proximity sensors

Contact proximity sensors

It is a device that consists of a rod that extends from one end and a switch or other linear position which monitors the element which is located within the body of the sensor. So when the robot manipulator moves, the sensor will be active only if the rod came into contact with an object.

Non-contact proximity sensors

In this type, the sensors are depended on a variety of operating principles to make the proximity determination. Reflected light, ultrasound are some of them

Accelerometers and gyroscopes

The accelerometer can measure the linear acceleration based on vibration while gyroscopes can be able to detect the orientation by using angular momentum.

Tactile sensors

Tactile sensors help the robots to touch and feel. Tactile sensors can be used for measuring applications and they would interact properly with the environment.

Eddy current sensors

These sensors are used as proximity switch and they operate on eddy current principle. These sensors will use a sensing coil to induce a high-frequency current in the target. The amplitude of the sensor-generated oscillations depends on the distance between the metal surface and the coil. The position can be obtained by monitoring the amplitude.

Conclusion

Today we find most robots working for people in industries, factories, warehouses, and laboratories. Robots are useful in many ways. For instance, it boosts economy because businesses need to be efficient to keep up with the industry competition. Therefore, having robots helps business owners to be competitive, because robots can do jobs better and faster than humans can, e.g. robot can built, assemble a car. Yet robots cannot perform every job; today robots roles include assisting research and industry. Finally, as the technology improves, there will be new ways to use robots which will bring new hopes and new potentials.

                     written by :- Dibakar Bera