Amin Mirfakhar

309 Paul Hall

6823 St Charles Ave

New Orleans, LA 70118

I am a Ph.D. candidate in Computer Science at Tulane University and a co-founder of Rebuildcobot, a startup focused on automation and robotics for the construction industry. My research spans additive manufacturing, optimization, robotics, and automation, with an emphasis on developing autonomous agents and robotic solutions for complex real-world tasks. Currently, under supervision of Prof. Ramgopal Mettu I’m exploring multi objective, non-planar 3D printing that goes beyond typical layer-based slicing to construct a toolpath.

Previously, I was an Automation Engineer at DSDAco. where i worked for almost 3 years on a number ot projects including programming a Six Degree of Freedom Motion Simulator, designing a Six Degree of Freedom Racing Car Motion Simulator, designing Camera and Illumination Housing for Harsh Environments, prototyping Conveyor Belt Condition Monitoring System, Green Iron Ore Pellet Size Detector and Control System, and Pipe Crawler Robot.

Prior to pursuing my PhD, I graduated with honors from Sharif University of Technology, earning a Master of Science in Mechatronics Engineering and a Bachelor of Science in a Mechanical Engineering.

selected publications

Control of a two-DOF parallel robot with unknown parameters using a novel robust adaptive approach

Saeed Ansari Rad, Mehran Ghafarian Tamizi, Amin Mirfakhar, and 2 more authors

ISA Transactions, 2021

Abs DOI PDF

Model-based methods lose their performance in confronting with model uncertainties and disturbances. Accordingly, some degrees of adaptation to the involved conditions are required. In this paper, a novel robust adaptive scheme is proposed which guarantees the simultaneous identification and control of a system in the presence of external disturbances. Thereafter, the suggested algorithm is implemented on a 2-DOf spherical parallel robot as a stabilizer device. By identifying unknown parameters of Jacobian matrix, the relative identification error is obtained as 0.0207. Applying external excitations to the base, the ratio of end-effector to base orientation is acquired as 0.091, demonstrating proper stabilization in comparison with other two well-known methods. The proposed structure also reveals a reliable performance in tracking desired paths for the end-effector Euler angles.