Amin Mardani

Amin Mardani is a researcher at ARAS Robotics Lab and an M.Sc student at K. N. Toosi University of Technology, Iran. His interest is in how robots interact with people, ranging from theory to design to implementation.

Amin Completed his B.Sc degree at Qom University of Technology, Iran. His field of study in both B.Sc and M.Sc is ‘control engineering’. He is currently a member of Autonomous Robotics group and is working in the field of Human-Robot Interactions (HRI).

Education
  • M.Sc in Electrical Engineering – Control

K. N. Toosi University of Technology, Tehran, Iran.

Supervisor: Prof. Taghirad

  • B.Sc in Electrical Engineering – Control

Qom University of Technology, Qom, Iran.

Thesis Title: Design and Implementation of a Non-Contact Rotary Torque Sensor

Supervisor: Prof. Nosrati

Skills
  • Programming Languages (Windows and Linux):
  1. Python
  2. C / C++
  3. MATLAB
  4. G
  • Microcontrollers and Practical Electronics:
  1. ARM (st)
  2. AVR
  3. PLC
  4. PCB Design and Assembly
  5. Electrical Circuits Design and Implement
  • Other Skills:
  1. Deep Learning
  2. Artificial Intelligence
Experiences
  • Linux ..
  • RA …
  • TA …
Current Project
  • Human-Robot Interaction
Design and develop algorithms for safe navigation of robots, especially social robots, in the presence of humans.

 

Mankind’s long-held dream is to build humanoid robots which interact well with people. Every day, human beings are completely subconsciously choosing their path of movement while noticing so many aspects, such as avoiding collisions with objects or other people, crossing smooth paths and achieving the desired goal, as well as observing many unwritten customary laws; yet robots do not know any of these rules.

It is desirable to see a human-like movement from robots, especially in the areas where people are present. The first step in imitating how humans move and behave is to identify and understand these behaviors. Vision is the most important sensation humans rely on to understand the environment, and for this reason, this sense has been the most studied in machine learning and artificial intelligence.

One of the most interesting areas in machine vision and robotics is the design of learning algorithms which have high accuracy, low computational complexity and enable autonomous mobile robots to operate in interactive visual environments. One of the most powerful tools available to researchers for this purpose is deep learning. The use of deep learning methods has been exploited in many real-world issues nowadays, and it is hoped that it will respond appropriately to this issue as well.

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