activity
20212026
collaborators

9 papers

cs.DC2026

Logarithmic-Time Geodesically Convex Decomposition in Programmable Matter

Henning Hillebrandt, Andreas Padalkin, Christian Scheideler +2

The decomposition of complex structures into simpler substructures is a powerful technique with a wide range of applications. We study the computation of decompositions in the cont…

cs.DS2026

Sublinear-Time Reconfiguration of Programmable Matter with Joint Movements

Manish Kumar, Othon Michail, Andreas Padalkin +1

We study centralized reconfiguration problems for geometric amoebot structures. A set of amoebots occupy nodes on the triangular grid and can reconfigure via expansion and cont…

cs.DC2025

Efficient Distributed Algorithms for Shape Reduction via Reconfigurable Circuits

Nada Almalki, Siddharth Gupta, Othon Michail +1

Autonomous reconfiguration of agent-based systems is a key challenge in the study of programmable matter, distributed robotics, and molecular self-assembly. While substantial prior…

cs.DC2025

On the Shape Containment Problem within the Amoebot Model with Reconfigurable Circuits

Matthias Artmann, Andreas Padalkin, Christian Scheideler

In programmable matter, we consider a large number of tiny, primitive computational entities called particles that run distributed algorithms to control global properties of the pa…

cs.DC2024

Polylogarithmic Time Algorithms for Shortest Path Forests in Programmable Matter

Andreas Padalkin, Christian Scheideler

In this paper, we study the computation of shortest paths within the \emph{geometric amoebot model}, a commonly used model for programmable matter. Shortest paths are essential for…

cs.RO2023

Reconfiguration and Locomotion with Joint Movements in the Amoebot Model

Andreas Padalkin, Manish Kumar, Christian Scheideler

We are considering the geometric amoebot model where a set of amoebots is placed on the triangular grid. An amoebot is able to send information to its neighbors, and to move vi…

cs.CG2023

Collision Detection for Modular Robots -- it is easy to cause collisions and hard to avoid them

Siddharth Gupta, Marc van Kreveld, Othon Michail +1

We consider geometric collision-detection problems for modular reconfigurable robots. Assuming the nodes (modules) are connected squares on a grid, we investigate the complexity of…

cs.DC2022

The Structural Power of Reconfigurable Circuits in the Amoebot Model

Andreas Padalkin, Christian Scheideler, Daniel Warner

The amoebot model [Derakhshandeh et al., 2014] has been proposed as a model for programmable matter consisting of tiny, robotic elements called amoebots. We consider the reconfigur…

cs.DC2021

Accelerating Amoebots via Reconfigurable Circuits

Michael Feldmann, Andreas Padalkin, Christian Scheideler +1

We consider an extension to the geometric amoebot model that allows amoebots to form so-called \emph{circuits}. Given a connected amoebot structure, a circuit is a subgraph formed…