The Internet Of Robotic Things(IoRT) Develop in order To Overcome The Limitations Of Networked Robotics.
The IoT system allows you to connect different things placed at different locations over the existing Internet or compatible network protocols. What if these “things” can possess their own Intelligence to decide the course of action in different scenarios?
Yes, that would tackle the issue of supporting control and monitoring activities at deployment sites and industrial automation. This concept is the Internet of Robotic Things(IoRT), where intelligent things can monitor peripheral events, induce sensor to collect Data from a variety of sources, use distribute machine intelligence.
to determine the appropriate course of action, and then act to control or disseminate static or dynamic robotic things aware in the physical world through a seamless manner by providing a means for utilizing them.
Impact of Robotics on Human Society
The Robotic System has brought tremendous changes in various socio-economical aspects of human society during the past decades. Robots have been widely deploy in various industries to perform repetitive, tedious, critical, and/or dangerous tasks, such as product assembly, car painting, box packaging, and dealing with harmful chemicals.
These pre-programmed robots have always been very successful at their accomplishments in all sorts of industries due to their high accuracy, precision, efficiency, speed, and productivity.
=Robotic technologies have been test upon with different available network technologies.
to extend the functionality range of these robots when deploy in undesirable environments for exploration and research purposes.
Networked Robots
A network of intelligent edge devices connect via wired or wireless communication is known as Networked Robotics System. Network robotics application can also be called remote-controlled robots i.e.
Robots which are control by human commands, or multi-network system which is a group of network robots deploy at different locations to perform different tasks by exchanging the sensor data and information use communication networks by self-cooperative manner to achieve the goal.
The Networked Robotics system has some limitations. such as low speed, onboard instruction execution, the small size of memory, network latency, variable quality of service, and lack of intelligence. These limitations gave birth to a new form of robotics that is IoRT.
How does IoRT work?
In this, the system relies upon centralize data processing warehouse infrastructure to access vast amounts of processing power.
data storage to support its operation that is not all computation and memory is integrate into a single stand-alone system. The basic principle behind IoRT and IoT is similar, where the cloud usually processes a large quantity of data for operating properly.
the “things” or robots have a small amount of place and energy for computing and data storage for taking decisions, visualizing issues, and patterns, steering processes and so forth. The robots are responsible for sensing, gathering data, analytics, and transmitting the information to the server.
Machine learning can also be implement for better processing of edge devices which would assist them in providing better output. Some advantages of IoRT are :
- Prevents the loss of data due to edge system failure.
- A large network of robots can provide more information during exploration at an unknown location.
- Self-assisted technology.
- It makes the system more reliable.
Architecture of IoRT
A three-layered architecture can deduce for the Internet of Robotic things:
1. Physical Layer
The physical layer mainly consists of sensors and actuators. These robots are intelligent enough to establish a multi-robot network and divide the tasks accordingly to serve the purpose of the operation. Sensors present in the physical layer are the devices that interact with the physical world and telemeters the environmental data. On the physical layer some actuators are present that are use to perform triggered actions.
2. Network and Control Layer
This layer includes modules, controllers, local and cloud data storage, as well as communication and control protocols. BLE, WiFi, and NFC – integrate for facilitating smooth connectivity between nearby robotic things. For the purpose of processing and storing data gather by sensors and actuators both, local and cloud storage are utilize.
3. Application and Service Layer
The implementation and execution of standard and user-define programs are performed.
in this layer by using actuators and sensors for controlling, processing, and monitoring the environmental parameters. This layer can also be utilized to implement various machine learning techniques and algorithms.
Applications of IoRT
One of the biggest applications of IoRT can be in a defense where these intelligent devices can be deployed on the battlefields to identify and neutralize the enemy.
These robots can be equip and train using machine learning to prevent mishappenings and decide an appropriate course of action in different situations. Also, they can be control from a far distance to tackle any unexpect situation giving an upper hand.
This would save thousands of lives lost at wars and robots can perform a particular task with more accuracy and precision. Though, We will need to consider some security issues to make them more durable and efficient.
Summary
So, in this IoRT tutorial, we went through the basics and impact of robotics. We understood the definition of IoRT, the working of IoRT, and the architecture of IoRT. We also went through the applications of IoRT in defense.
As a Robotics enthusiast, researching on IoRT and then implementing. it can give you an upper hand in today’s evolving world.
IoRT is a network of intelligent things enabling advance robotics services by interconnecting robotic things. based on existing communication protocols allowing robots to take benefits of powerful computational and shared data storage within a compact size.
This is the right time to learn and use IoRT as this technology is still under development and full of future possibilities. Hope the tutorial was helpful. If there is anything we miss out on, inform us in the comments section.
Written by: Harshit Goel
Reviewed by: Batta Pruthvi
If you are Interested In Machine Learning You Can Check Machine Learning Internship Program
Also Check Other Technical And Non Technical Internship Programs