282 citations · 348 across the 18 of their papers we have counts for
8 papers · 1 filter
Supervisory Coordination of Robotic Fiber Positioners in Multi-Object Spectrographs
Matin Macktoobian, Denis Gillet, Jean-Paul Kneib
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 sp…
Self-organizing nest migration dynamics synthesis for ant colony systems
Matin Macktoobian
In this study, we synthesize a novel dynamical approach for ant colonies enabling them to migrate to new nest sites in a self-organizing fashion. In other words, we realize ant col…
Learning convergence prediction of astrobots in multi-object spectrographs
Matin Macktoobian, Francesco Basciani, Denis Gillet +1
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…
Astrobotics: Swarm Robotics for Astrophysical Studies
Matin Macktoobian, Denis Gillet, Jean-Paul Kneib
This paper introduces the emerging field of astrobotics, that is, a recently-established branch of robotics to be of service to astrophysics and observational astronomy. We first d…
Automatic Reconfiguration of Untimed Discrete-Event Systems
Matin Macktoobian, W. Murray Wonham
This work introduces a general formulation of the reconfiguration problem for untimed discrete-event systems (DES), which can be treated directly by supervisory control theory (SCT…
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 approac…
Meta Navigation Functions: Adaptive Associations for Coordination of Multi-Agent Systems
Matin Macktoobian, Guillaume Ferdinand Duc
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 con…
Learning Optimal Topology for Ad-hoc Robot Networks
Matin Macktoobian, Zhan Shu, Qing Zhao
In this paper, we synthesize a data-driven method to predict the optimal topology of an ad-hoc robot network. This problem is technically a multi-task classification problem. Howev…