arXiv subjects

Loona Macabre

Publications and source records attributed to Loona Macabre.

3 recordsLinked to original sources

arXiv2025

Pogosim -- a Simulator for Pogobot robots

Pogobots are a new type of open-source/open-hardware robots specifically designed for swarm robotics research. Their cost-effective and modular design, complemented by vibration-based and wheel-based locomotion, fast infrared communication and extensive software architecture facilitate the implementation of swarm intelligence algorithms. However, testing even simple distributed algorithms directly on robots is particularly labor-intensive. Scaling to more complex problems or calibrate user code parameters will have a prohibitively high strain on available resources. In this article we present Pogosim, a fast and scalable simulator for Pogobots, designed to reduce as much as possible algorithm development costs. The exact same code will be used in both simulation and to experimentally drive real robots. This article details the software architecture of Pogosim, explain how to write configuration files and user programs and how simulations approximate or differ from experiments. We describe how a large set of simulations can be launched in parallel, how to retrieve and analyze the simulation results, and how to optimize user code parameters using optimization algorithms.

cs.RO↗

arXiv2025

Pogobot: an Open-Source, Low-Cost Robot for Swarm Robotics and Programmable Active Matter

This paper describes the Pogobot, an open-source platform specifically designed for research at the interface of swarm robotics and active matter. Pogobot features vibration-based or wheel-based locomotion, fast infrared communication, and an array of sensors in a cost-effective package (approx. 250euros/unit). The platform's modular design, comprehensive API, and extensible architecture facilitate the implementation of swarm intelligence algorithms and collective motion. Pogobots offer an accessible alternative to existing platforms while providing advanced capabilities including directional communication between units and fast locomotion, all with a compact form factor. More than 200 Pogobots are already being used on a daily basis in several Universities to study self-organizing systems, programmable active matter, discrete reaction-diffusion-advection systems and computational models of social learning and evolution. This paper details the hardware and software architecture, communication protocols, locomotion mechanisms, and the infrastructure built around the Pogobots.

cs.RO↗

arXiv2024

Signaling and Social Learning in Swarms of Robots

This paper investigates the role of communication in improving coordination within robot swarms, focusing on a paradigm where learning and execution occur simultaneously in a decentralized manner. We highlight the role communication can play in addressing the credit assignment problem (individual contribution to the overall performance), and how it can be influenced by it. We propose a taxonomy of existing and future works on communication, focusing on information selection and physical abstraction as principal axes for classification: from low-level lossless compression with raw signal extraction and processing to high-level lossy compression with structured communication models. The paper reviews current research from evolutionary robotics, multi-agent (deep) reinforcement learning, language models, and biophysics models to outline the challenges and opportunities of communication in a collective of robots that continuously learn from one another through local message exchanges, illustrating a form of social learning.

cs.RO↗