Challenges for Novice Developers in Rough Terrain Rescue Robots: A Survey on Motion Control Systems

Several researchers have revealed the huge potentials of rescue robots in disaster zones.

In addition to searching for victims, these intelligent machines are also effective in obtaining useful information from the zones, these functions help to optimize the search and rescue missions. 

However, the fact that rescue robots have to operate in risky and dangerous environments necessitates the need for such machines to have an efficient motion control system, which can help them to operate autonomously or with minimal human control.

This paper reviews the use of reliable controllers in enhancing the sensing capabilities of rescue robots.

The huge potential of sensorless sensing method in the rescue robots is highlighted.

It is shown that the use of sensorless sensing method enables developer to create simple and cheaper robots for various complex situations.

Thus, it is imperative to conduct further studies on how to optimize the operations of robots that lack sensors.

Conference: “Future of Artificial Intelligence, Automation & Robotics”Important Dates: October 22-23, 2020Venue: Rome, Italy

CONTACT :

killada P

longdom Conference Manager

Ph no: +3280075358

Whatsapp no: +32466903217

Mail id: roboticscongress@longdommeetings.com

Investigation on chatter stability of robotic rotary ultrasonic milling

In recent years, industrial robots with higher flexibility and lower cost have become a hot topic in the manufacturing field.

In terms of practical machining applications, they are mainly employed in situations with low cutting forces such as deburring, chamfering and polishing. However, the weak stiffness of robot induces milling chatter easily.

 Severe chatter not only damages the dimensional accuracy of parts but also decreases machining efficiency and tool life.

 Thus, it is urgent to seek a new method to suppress robotic milling chatter. In this paper, robotic rotary ultrasonic milling (RRUM) technology is used to restrict machining vibration. Meantime, an analytical model of stability is developed.

The robotic milling system is considered as three degrees of freedom (3-DOF) model. After that, based on the analysis of dynamic chip thickness, a linear force model is developed through defining an angle γ affected by ultrasonic vibration.

Then, the semi-discretization method (SDM) is applied to obtain stability lobe diagrams.

The analysis result indicates that the stability region of RRUM is improved by 133% compared with robotic conventional milling (RCM).

Finally, verification experiments are carried out to prove the rationality and effectiveness of these stability lobe diagrams.

Longdom conferences are offering a "Future of Artificial intelligence, Automation, and Robotics" conference to discuss the adoption of research works in every field related to robotics and artificial intelligence.

Visit our website: https://www.longdom.com/robotics

CONTACT:

Killada P

Conference service Manager
Robo Talks 2020

Longdom Conferences
Contact no: +32466903217

WhatsApp no: +32466903217

Artificial Intelligence and Expert Systems

In the geographical analysis, the demand for domain-specific knowledge, technical know-how, and accessibility to data is tremendous. 

It is difficult to make good decisions without powerful systems to provide, in an integrative way supports in various phases of the decision-making process.

A decision support system has to possess intelligence to handle information efficiently and to apply the right kind of structured, semi structured, and loosely structured knowledge, to assist the decision-making process in a user-friendly manner.

Their development calls for the utilization of artificial intelligence and expert system methods to represent and infer with spatial knowledge; to manage systems development, information, and control flows of models and data; and spatial information system technologies to process and display data.

All these have to be integrated in a seamless manner, Knowledge representation and inference, the key components of an expert system, are of paramount importance in spatial reasoning.

With the above background, this article examines the development of expert systems and spatial decision support systems for solving complex spatial decision-making problems.

It discusses the fundamentals of expert systems and the general approach to the development of intelligent spatial decision support systems.

The role of artificial intelligence in this area of research is scrutinized. The potential contribution of knowledge discovery from open and big data to the development of intelligent systems is also highlighted.

We are fulfilled to welcome you to visit and interface with us at the Future of Artificial Intelligence, Automation, and Robotics on October 22-23, 2020 in Rome, Italy.

CONTACT:

Killada P

Conference service Manager
Robo Talks 2020

Longdom Conferences
Contact no: +32466903217

WhatsApp no: +32466903217

Evolutional Methods for Creating Artificial Intelligence of Robotic Technical Systems

This paper considers evolutionary methods of symbolic regression for the creation of artificial intelligence of robotic systems. 

Methods of symbolic regression are reviewed and the features of their application to the solution of the problem of synthesis of control of robotic systems are indicated. 

The measure of the complexity of artificial intelligence is determined and the advantage of using the principle of small variations of the basic solution is shown while creating intelligent control systems.

 A method of variational analytic programming is described and an example of its use for the synthesis of intellectual control is given.

Conference: “Future of Artificial Intelligence, Automation & Robotics”
Important Dates: October 22-23, 2020
Venue: Rome, Italy

CONTACT:

killada P

longdom Conference Manager

Ph no: +3280075358

Whatsapp no: +32466903217

Mail id: roboticscongress@longdommeetings.com

Autonomic machine learning platform

Acquiring information properly through machine learning requires familiarity with the available algorithms and understanding how they work and how to address the given the problem in the best possible way.

However, even for machine-learning experts in specific industrial fields, in order to predict and acquire information properly in different industrial fields, it is necessary to attempt several instances of trial and error to succeed with the application of machine learning. For non-experts, it is much more difficult to make accurate predictions through machine learning.

In this paper, we propose an autonomic machine learning platform which provides the decision factors to be made during the developing of machine learning applications. In the proposed autonomic machine learning platform, machine learning processes are automated based on the specification of autonomic levels.

This autonomic machine learning platform can be used to derive a high-quality learning result by minimizing experts’ interventions and reducing the number of design selections that require expert knowledge and intuition. We also demonstrate that the proposed autonomic machine learning platform is suitable for smart cities which typically require considerable amounts of security sensitive information.

Conference: “Future of Artificial Intelligence, Automation & Robotics”
Important Dates: October 22-23, 2020
Venue: Rome, Italy

CONTACT:

killada P

longdom Conference Manager

Ph no: +3280075358

Whatsapp no: +32466903217

Mail id: roboticscongress@longdommeetings.com

The state of the art of testing standards for integrated robotic systems

Technology standards facilitate the transparency in the market and the supplies of products with good quality.
For manufacturers, standards make it possible to reduce the costs by mass production and enhance system adaptabilities through integrating system modules with the standardized interfaces.
However, international standards on industrial robots such as ISO-9283 were developed in 1998, and they have not updated since then.
Due to the ever-increasing applications of robots in complex systems, there is an emerging need to advance existing standards on robots for a broader scope of system components and system integration.
This paper gives an introduction to the endeavors by the National Institute of Standards and Technology (NIST); especially, it overviews the recent signs of progress on the standardized tests of robotic systems and components.
The presented work aims to identify the limitations of existing industry standards and clarify the trend of technology standardizations for industrial robotic systems.

Conference: “Future of Artificial Intelligence, Automation & Robotics”
Important Dates: October 22-23, 2020
Venue: Rome, Italy

CONTACT:

killada P

longdom Conference Manager

Ph no: +3280075358

Whatsapp no: +32466903217

Mail id: roboticscongress@longdommeetings.com

Challenges for Novice Developers in Rough Terrain Rescue Robots: A Survey on Motion Control Systems

Several researchers have revealed the huge potentials of rescue robots in disaster zones. In addition to searching for victims, these intelligent machines are also effective in obtaining useful information from the zones.

These functions help to optimize the search and rescue missions. However, the fact that rescue robots have to operate in risky and dangerous environments necessitates the need for such machines to have an efficient motion control system, which can help them to operate autonomously or with minimal human control.

This paper reviews the use of reliable controllers in enhancing the sensing capabilities of rescue robots.

The huge potential of sensorless sensing method in the rescue robots is highlighted. It is shown that the use of sensorless sensing method enables developer to create simple and cheaper robots for various complex situations.

Thus, it is imperative to conduct further studies on how to optimize the operations of robots that lack sensors.

Conference: “Future of Artificial Intelligence, Automation & Robotics”
Important Dates: October 22-23, 2020
Venue: Rome, Italy.

CONTACT:

killada P

longdom Conference Manager

Ph no: +3280075358

Whatsapp no: +32466903217

Mail id: roboticscongress@longdommeetings.com