Matan Yah Ben Zion
Assistant Professor
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About
Dr. Matan Yah Ben Zion is an Assistant Professor at Radboud Universiteit Nijmegen, Netherlands. His research focuses on autonomous robotic swarms, including topics such as swarm cohesion, cooperative transport, and morphological computation. He has published extensively on hydrodynamic phenomena in micro-rotors and the dynamic behaviors of colloidal gels and hybrid colloidal systems.
Articles (10)
Year:
2025
Year:
2025
Year:
2024
Whereas naturally occurring swarms thrive when crowded, physical interactions in robotic swarms are either avoided or carefully controlled, thus limiting their operational density. Here, we present a mechanical design rule that allows robots to act in a collision-dominated environment. We introduce Morphobots, a robotic swarm platform developed to implement embodied computation through a morpho-functional design. By engineering a three-dimensional printed exoskeleton, we encode a reorientation response to an external body force (such as gravity) or a surface force (such as a collision). We show that the force orientation response is generic and can augment existing swarm robotic platforms (e.g., Kilobots) as well as custom robots even 10 times larger. At the individual level, the exoskeleton improves motility and stability and also allows encoding of two contrasting dynamical behaviors in response to an external force or a collision (including collision with a wall or a movable obstacle and on a dynamically tilting plane). This force orientation response adds a mechanical layer to the robot’s sense-act cycle at the swarm level, leveraging steric interactions for collective phototaxis when crowded. Enabling collisions also promotes information flow, facilitating online distributed learning. Each robot runs an embedded algorithm that ultimately optimizes collective performance. We identify an effective parameter that controls the force orientation response and explore its implications in swarms that transition from dilute to crowded. Experimenting with physical swarms (of up to 64 robots) and simulated swarms (of up to 8192 agents) shows that the effect of morphological computation increases with growing swarm size.
Year:
2023
Year:
2023
Year:
2023
Year:
2022
Year:
2022
Year:
2021
Year:
2020
Collaborators (4)
Guolong Zhu
Assistant Professor of Physics
Fairleigh Dickinson University
David G. Grier
New York University
Kyle J. M. Bishop
Columbia University
Olivier Dauchot
PSL Research University
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