Perception and Robotics: AI's Role in Technological Advancements

This report delves into the relationship between perception and robotics, highlighting the significant impact of artificial intelligence and machine learning on enhancing robotic capabilities. It discusses how AI algorithms enable machines to mimic human-like behaviors, and examines key contributions in the field, including the Strands, RobDREAM, SPENCER, and AUTOCITS projects. These projects showcase advancements in human-robot interaction, dynamic environment navigation, social awareness, and automated driving. The report emphasizes the importance of these developments in bridging the gap between humans and robots, allowing robots to perform complex tasks in real-world scenarios. The integration of perception, driven by AI, is presented as a crucial element in the evolution of robotics, enabling robots to interact more effectively with their surroundings and with humans.

Running head: PERCEPTION AND ROBOTICS
PERCEPTION AND ROBOTICS
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1PERCEPTON AND ROBOTICS
Perception is the term that refers to the ability to understand particular information or an
environment. Perception is present among living things, besides this, the concept of perception is
also included in modern technology. Here various technologies are involved that resulted to
impose perception among various devices with the use of technology (Harris et al., 2018). In this
case, there is a certain ability that is imposed among the devices that lead the devices to have
certain skills related to the living organisms. Technology has resulted in various changes in the
environment, including perception among no living things is one of such.
Robotics is considered to be a part of engineering and science where technologies of
various fields are involved that includes computer science, electronic engineering, mechanical
engineering and many other technologies as we. The design is one of the important parts of
robotics, besides thus the robots are needed to construct and operated (Ruhland et al., 2015).
Various technoloies are nvolved which results in the machnines to behave like human beings.
There are different types of robotics which are of different design and technology. They are also
intended to perform various types of activities. They are built for various purposes.
Robotics and perception are the terms that are related to one other, as technology tries to
include perception among the robots. Due to this, the robots will have certain abilities that are
similar to living beings. Among all the contributions that lead to the success of including
perception in robotics is the use of artificial intelligence and machine learning. In the case of AI
and machine learning various types of computer algorithms are used which are included in the
computer system of the robot. Various type of information is included in the algorithm which
teaches the devices to perform as such (Kehoe, 2015). Artificial intelligence is the concept of
imposing man-made intelligence aiming machines which leads the machines to behave like
human beings. In machine learning various activities are taught t the machines which involving

2PERCEPTON AND ROBOTICS
the algorithm, due to this perception is added among the machines. Thus this is an important
contribution in the field of perception and robotics.
Another important contribution to this field is the implementation of the Strands project.
With the help of this project, the robots were capable to operate their own along with human
beings. Ths this is the project which resulted in the field of robotics to another step (Ghahramani,
2015). Due to this project, enough contributions are gained and thus it fulfilled the gap in
between the human and robot, due to this the robots can easily perform useful activities in real-
life f their own. Thus due to this result, it is considered one of the biggest contributions in the
field of perception and robotics.
Another important contribution in this field is considered to be the RobDREAM project.
The project has mainly focused on the advanced world f robotics where the robots can operate in
various dynamic environments and complex environments and due to this, the involvement of
perception is needed among robotics (Maitra & Mani, 2017). Thus they have worked on this
particular aim which also resulted in certain capabilities among the robots. They can analyze
various real-life scene, they can also recognize the various type of objects and can even
manipulate the objects. Due to this certain works the project act as a very important contribution
in the field of perception and robotics.
Another important project is the SPENCER project where the robots are involved with
the environment where they can interact with nature along with numerous kind 9f human beings
(Premebida, Ambrus & Marton, 2018). This is a very important factor because when perception
is concerned among the robots it is necessary to behave like human beings in the open
environment as well. The project tried to make their functionalities more efficient and this can be

3PERCEPTON AND ROBOTICS
only done when they are more connected to the real world and due to this they focused on the
term "socially aware". In this case, the robots will have certain perception skills besede to this
which are also efficient in the open world as well. Thus this is considered one of the important
contributions in the field of perception and robotics.
Another important project, in this case, is the AUTOCITS project which aimed at
automated driving with the help of robots and thus interchanging with the real-life pilots. They
have used numerous technologies that helped them to impose automated driving robots. This is
one of the important contributions in the field of perception in robotics.

4PERCEPTON AND ROBOTICS
Reference:
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Harris, J. L., Vendely, M. J., Kwee, N. Y., & Shelton IV, F. E. (2018). U.S. Patent Application
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Kehoe, B., Patil, S., Abbeel, P., & Goldberg, K. (2015). A survey of research on cloud robotics
and automation. IEEE Transactions on automation science and engineering, 12(2), 398-
409.
Maitra, P., & Mani, S. (2017). Learning and earning: Evidence from a randomized evaluation in
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Premebida, C., Ambrus, R., & Marton, Z. C. (2018). Intelligent Robotic Perception Systems.
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Ruhland, K., Peters, C. E., Andrist, S., Badler, J. B., Badler, N. I., Gleicher, M., ... & McDonnell,
R. (2015, September). A review of eye gaze in virtual agents, social robotics and hci:
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