Mohammad Mohammadpour | Motion planning | Best Researcher Award

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Dr. Mohammad Mohammadpour | Motion planning| Best Researcher Award

Ā Dr. University of Quebec at Trois-RiviĆØres, Canada

šŸ‘©ā€šŸ”¬ Ph.D. in Mechanical Engineering with over eight years of specialized experience in R&D, contributing to cutting-edge projects at two renowned institutions.

 

Profile

Scopus

 

Education šŸŽ“

Ph.D. in Mechanical Engineering (Robotics), University of Quebec at Trois RiviĆØres, QC, Trois RiviĆØres, Canada; May 2019-Feb 2024Masterā€™s degree in Aerospace Engineering (Flight Dynamic & Control), Amirkabir University of Technology, Tehran, Iran; 2014Bachelor’s degree in Mechanical Engineering, Tehran, Iran; 2011

Skills šŸ› ļø

Programming Language: Python, C++Software: ROS, Gazebo, Rviz, MATLAB & Simulink Research: Navigation and Sensor Data Fusion Motion Planning (Guidance)Movement Sciences (Kinetic & Kinematic)Dynamic Modelling and Control Machine Learning and Deep Learning Obstacle Avoidance Applications: Autonomous Mobile Robots (simulation and experiment)Learning Frameworks: Scikit-learn, Keras, TensorFlow

Experience šŸš€ Robotics Engineer

Hydrogen Research Institute, University of Quebec at Trois RiviĆØres, Trois RiviĆØres, QC, Canada; 2019-2024Dynamic modeling, simulating, and analyzing robotsā€™ motion Implementing motion planning (guidance) algorithms on an Autonomous Mobile Robot and an Autonomous Forklift (simulation and experiment)Developing motion planning (guidance) algorithms using deep neural networks and the robotsā€™ kinetic models (simulation and experiment)Designing and implementing motion controllers (simulation and experiment). Research And Development Engineer Research Center of Amirkabir University of Technology, Tehran, Iran; 2015-2019Contributed to the Attitude Determination And Control System Executed MIL, SIL, PIL, and HIL simulation and testing Conducted operation and calibration tests of sensors Participated in dynamic modelling

Publications Top Notes šŸ“

i. Energy-efficient motion planning of an autonomous forklift using deep neural networks and kinetic model, Authors: M. Mohammadpour et al., 2023

 

ii. Energy-efficient Local Path Planning of a Self-Guided Vehicle by Considering the Load Position, Authors: Not provided, 2022

 

iii. An Investigation into the Energy-Efficient Motion of Autonomous Wheeled Mobile Robots, Authors: M. Mohammadpour et al., 2021