Publications by Matin Macktoobian

Data-Driven Convergence Prediction of Astrobots Swarms

Denis Gillet, Jean-Paul Richard Kneib, Matin Macktoobian, Francesco Basciani

Astrobots are robotic artifacts whose swarms are used in astrophysical studies to generate the map of the observable universe. These swarms have to be coordinated with respect to various desired observations. Such coordination\footnote{\z{A coordination sa ...

2022

Meta Navigation Functions: Adaptive Associations for Coordination of Multi-Agent Systems

Matin Macktoobian

In this paper, we introduce a new class of potential fields, i.e., meta navigation functions (MNFs) to coordinate multi-agent systems. Thanks to the MNF formulation, agents can contribute to each other's coordination via partial and/or total associations, ...

IEEE2022

Analytical and Machine Learning Methods for the Complete Safe Coordination of Astrobot Swarms

Matin Macktoobian

The recent generations of massive spectroscopic surveys aim at the ray collection from a multitude of cosmological targets in the course of observations. For this purpose, astrobots are used to change the configuration of optical fibers from one observatio ...

EPFL2021

Astrobotics: Swarm Robotics for Astrophysical Studies

Denis Gillet, Jean-Paul Richard Kneib, Matin Macktoobian

2021

Learning convergence prediction of astrobots in multi-object spectrographs

Denis Gillet, Jean-Paul Richard Kneib, Matin Macktoobian, Francesco Basciani

Astrobot swarms are used to capture astronomical signals to generate the map of the observable universe for the purpose of dark energy studies. The convergence of each swarm in the course of its coordination has to surpass a particular threshold to yield a ...

2021

Reconfigurable Timed Discrete-Event Systems

Matin Macktoobian

In this paper, we present the first general solution to the automatic reconfiguration problem of timed discrete-event systems. We extend the recursive forcible backtracking approach which had been already solved the automatic reconfiguration problem of unt ...

IEEE2020

Optimal target assignment for massive spectroscopic surveys

Denis Gillet, Jean-Paul Richard Kneib, Matin Macktoobian

Robotics have recently contributed to cosmological spectroscopy to automatically obtain the map of the observable universe using robotic fiber positioners. For this purpose, an assignment algorithm is required to assign each robotic fiber positioner to a t ...

2020

Experimental evaluation of complete safe coordination of astrobots for Sloan Digital Sky Survey V

Denis Gillet, Jean-Paul Richard Kneib, Mohamed Bouri, Ricardo Jorge Araùjo Pereira, Matin Macktoobian, Luzius Gregor Kronig, Loïc Grossen

The data throughput of massive spectroscopic surveys in the course of each observation is directly coordinated with the number of optical fibers which reach their target. In this paper, we evaluate the safety and the performance of the astrobots coordinati ...

2020

The Navigation of Robotic Fiber Positioners in SDSS-V Project: Design and Implementation

Denis Gillet, Jean-Paul Richard Kneib, Matin Macktoobian

SDSS-V project is one of the major observational cosmological projects which aims to generate the map of the observable universe by collecting spectroscopic data from the sky using optical fibers. Each optical fiber is attached to a robotic positioner to b ...

IEEE2019

Supervisory Coordination of Robotic Fiber Positioners in Multi-Object Spectrographs

Denis Gillet, Jean-Paul Richard Kneib, Matin Macktoobian

In this paper, we solve the complete coordination problem of robotic fiber positioners using supervisory control theory. In particular, we model positioners and their behavioral specifications as discrete-event systems by the discretization of their motion ...

Elsevier2019