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Communication-based Swarming for Flying Robots
Related publications (42)
Human-Robot Swarm Interaction: An Explorative Path to Foster Complex Systems Understanding
Order, regularities, and patterns are ubiquitous around us. A flock of birds maneuvering in the sky, the self-organization of social insects, a global pandemic or a traffic jam are examples of complex systems where the macroscopic patterns arise from the m ...
EPFL2023Model Predictive Control of Aerial Swarms
Aerial robot swarms can have a large socio-economic impact. They can perform time-critical missions faster than a single robot and access dangerous environments without compromising human safety. However, swarm deployment is often limited to free environme ...
EPFL2022Swarms of flying robots in unknown environments
An optimal planning algorithm enables swarms of flying robots to explore unknown environments autonomously and safely. ...
AMER ASSOC ADVANCEMENT SCIENCE2022Vision-based Flocking in Aerial Robot Swarms
Aerial robot swarms have the potential to perform time-critical and dangerous tasks such as disaster response without compromising human safety. However, their reliance on external infrastructure such as global positioning for localization and wireless net ...
EPFL2022Robust Localization for Multi-robot Formations: An Experimental Evaluation of an Extended GM-PHD Filter
Alcherio Martinoli, Alicja Barbara Roelofsen, Michiaki Hirayama
This paper presents a thorough experimental evaluation of an extended Gaussian Mixture Probability Hypothesis Density filter which is able to provide state estimates for the maintenance of a multirobot formation, even when the communication fails and the t ...
Springer Nature2021Electroencephalography as implicit communication channel for proximal interaction between humans and robot swarms
Francesco Mondada, Mohammad Ehsanul Karim
Search and rescue, autonomous construction, and many other semi-autonomous multi-robot applications can benefit from proximal interactions between an operator and a swarm of robots. Most research on proximal interaction is based on explicit communication t ...
Springer Verlag2016A Distributed Noise-Resistant Particle Swarm Optimization Algorithm for High-Dimensional Multi-Robot Learning
Alcherio Martinoli, Inaki Navarro Oiza, Ezequiel Leonardo Di Mario
Population-based learning techniques have been proven to be effective in dealing with noise in numerical benchmark functions and are thus promising tools for the high-dimensional optimization of controllers for multiple robots with limited sensing capabili ...
2015Distributed vs. Centralized Particle Swarm Optimization for Learning Flocking Behaviors
Alcherio Martinoli, Inaki Navarro Oiza, Ezequiel Leonardo Di Mario
In this paper we address the automatic synthesis of controllers for the coordinated movement of multiple mobile robots. We use a noise-resistant version of Particle Swarm Optimization to learn in simulation a set of 50 weights of a plastic artificial neura ...
The MIT Press2015Science, technology and the future of small autonomous drones
We are witnessing the advent of a new era of robots — drones — that can autonomously fly in natural and man-made environments. These robots, often associated with defence applications, could have a major impact on civilian tasks, including transportation, ...
Nature Publishing Group2015Distributed Learning of Cooperative Robotic Behaviors using Particle Swarm Optimization
Alcherio Martinoli, Inaki Navarro Oiza, Ezequiel Leonardo Di Mario
In this paper we study the automatic synthesis of robotic controllers for the coordinated movement of multiple mobile robots. The algorithm used to learn the controllers is a noise-resistant version of Particle Swarm Optimization, which is applied in two d ...
2014