Amirhassan Monadjemi

About

Amirhassan Monadjemi is a robotics researcher whose work focuses on energy-efficient mobile robot design, autonomous navigation, and vision-based perception. His most notable contribution is the development of a two-pendulum Innovative Spherical Robot (ISR), detailed in his highly cited 2019 paper (28 citations). This design achieves 11% greater energy efficiency by decoupling lateral and longitudinal motion, addressing a critical challenge in spherical robot autonomy. Monadjemi also advances computer vision for robotics, including entrance detection in outdoor scenes (11 citations) and curvilinear path feature extraction for humanoid navigation using monocular vision. His recent work on automatic parallel parking using artificial neural networks (2024) demonstrates continued innovation in applying machine learning to real-world robotic tasks. With a research portfolio spanning dynamic modeling, visual perception, and neural control, Monadjemi contributes practical solutions that enhance robot autonomy and efficiency, making his work valuable for students and researchers in mobile robotics and intelligent systems.

Research Focus

Key Achievements

Top Papers

1. 1
   The Design and Development of a Dynamic Model of a Low-Power Consumption, Two-Pendulum Spherical Robot

   28 citations · 2019
2. 2
   Vision-based entrance detection in outdoor scenes

   11 citations · 2018
3. 3
   AUTOMATIC ROBOT CAR PARALLEL PARKING SYSTEM USING ARTIFICIAL NEURAL NETWORK

   2 citations · 2024
4. 4
   Finding Curvilinear Path Features in a Layered Learning Paradigm for Humanoid Robot Using Monocular Vision

   2 citations · 2014

Key Collaborators

Contact & Links