Marco Dorigo

Université Libre de Bruxelles | ULB · Artificial Intelligence Research Laboratory of the Université Libre de Bruxelles (IRIDIA)

In collective perception, agents sample spatial data and use the samples to agree on some estimate. In this paper, we identify the sources of statistical uncertainty that occur in collective perception and note that improving the accuracy of fully decentralized approaches, beyond a certain threshold, might be intractable. We propose self-organizing...

Through cooperation, robot swarms can perform tasks or solve problems that a single robot from the swarm could not perform/solve by itself. However, it has been shown that a single Byzantine robot (such as a malfunctioning or malicious robot) can disrupt the coordination strategy of the entire swarm. Therefore, a versatile swarm robotics framework...

Hierarchical frameworks—a special class of directed frameworks with a layer-by-layer architecture—can be an effective mechanism to coordinate robot swarms. Their effectiveness was recently demonstrated by the mergeable nervous systems paradigm (Mathews et al., 2017), in which a robot swarm can switch dynamically between distributed and centralized...

Self-organized groups of robots have generally coordinated their behaviors using quite simple social interactions. Although simple interactions are sufficient for some group behaviors, future research needs to investigate more elaborate forms of coordination, such as social cognition, to progress towards real deployments. In this perspective, we de...

This paper addresses formation control of underactuated autonomous underwater vehicles in three-dimensional space, using a hybrid protocol that combines aspects of centralized and decentralized control with constraints that are particular to underwater vehicles, including switching topologies, unmeasurable velocities, and system constraints. Using...

We study how robot swarms can achieve a consensus on the best among a set of n possible options available in the environment. While the robots rely on local communication with one another, follow simple rules, and make estimates of the option’s qualities subject to measurement errors, the swarm as a whole is able to make accurate collective decisio...

Most of our experiences, as well as our intuition, are usually built on a linear understanding of systems and processes. Complex systems in general, and more specifically swarm robotics in this context, leverage non-linear effects to self-organize and to ensure that ‘more is different’. In previous work, the non-linear and therefore counter-intuiti...

We present a novel control scheme for robot swarms that exploits the computation layer of a blockchain to coordinate the actions of individual robots in real-time. To accomplish this, we deploy a blockchain smart contract that acts as a “decentralized supervisor” during a swarm foraging task. Our results show that using blockchain-based global coor...

In this study, we investigate the emergence of naming conventions within a swarm of robots that collectively forage, that is, collect resources from multiple sources in the environment. While foraging, the swarm explores the environment and makes a collective decision on how to exploit the available resources, either by selecting a single source or...

Programming robot swarms is hard because system requirements are formulated at the swarm level (i.e., globally) while control rules need to be coded at the individual robot level (i.e., locally). Connecting global to local levels or vice versa through mathematical modeling to predict the system behavior is generally assumed to be the grand challeng...

Quadrotors are a versatile and popular category of Unmanned Aerial Vehicles (UAVs). They can take off and land vertically and perform sophisticated maneuvers, while still being relatively small in size with a simple structure and low maintenance costs. They are also easily accessible due to the availability of off-the-shelf components and open-sour...

We present a rigorous, component‐based analysis of six widespread metaphor‐based algorithms for tackling continuous optimization problems. In addition to deconstructing the six algorithms into their components and relating them with equivalent components proposed in well‐established techniques, such as particle swarm optimization and evolutionary a...

The current state of the art in cognitive robotics, covering the challenges of building AI-powered intelligent robots inspired by natural cognitive systems. A novel approach to building AI-powered intelligent robots takes inspiration from the way natural cognitive systems—in humans, animals, and biological systems—develop intelligence by exploiting...

It has been more than 10 years since the first version of cuckoo search was proposed by Yang and Deb and published in the proceedings of the World Congress on Nature & Biologically Inspired Computing, in 2009. The two main articles on cuckoo search have now been cited almost 8 700 times (according to Google scholar), there are books and chapters pu...

Swarm intelligence studies self-organized collective behavior resulting from interactions between individuals, typically in animals and artificial agents. Some studies from cognitive science have also demonstrated self-organization mechanisms in humans, often in pairs. Further research into the topic of human swarm intelligence could provide a bett...

The particle swarm optimization (PSO) algorithm has been the object of many studies and modifications for more than twentyfive years. Ranging from small refinements to the incorporation of sophisticated novel ideas, the majority of modifications proposed to this algorithm have been the result of a manual process in which developers try new designs...

The importance of swarm robotics systems in both academic research and real-world applications is steadily increasing. However, to reach widespread adoption, new models that ensure the secure cooperation of large groups of robots need to be developed. This work introduces a method to encapsulate cooperative robotic missions in an authenticated data...

Swarm robotics deals with the design, construction, and deployment of large groups of robots that coordinate and cooperatively solve a problem or perform a task. It takes inspiration from natural self-organizing systems, such as social insects, fish schools, or bird flocks, characterized by emergent collective behavior based on simple local interac...

This paper demonstrates a swarm robotics construction system where the intelligence that coordinates construction has been moved from the robots to an advanced building material. This building material, that we call Stigmergic Blocks, is capable of computation and local communication. Using comprehensive simulation models based on real hardware, we...

Ant colony optimization (ACO) algorithms have originally been designed for static optimization problems, where the input data is known in advance and is not subject to changes over time. Later, the long term memory of ACO proved effective for reoptimization over environment changes when extended to deal with dynamic combinatorial optimization probl...

Swarm robotics will tackle real-world applications by leveraging automatic design, heterogeneity, and hierarchical self-organization.

Building structures is a remarkable collective process but its automation remains an open challenge. Robot swarms provide a promising solution to this challenge. However, collective construction involves a number of difficulties regarding efficient robots allocation to the different activities, particularly if the goal is to reach an optimal constr...

We propose an approach to multi-robot coverage that combines aspects of centralized and decentralized control, based on the existing ‘mergeable nervous systems’ concept. In our approach, robots self-organize a dynamic ad-hoc communication network for distributed asymmetric control, enabling a degree of central coordination. In the coverage task, si...

The research topic of human–human swam intelligence includes many mechanisms that need to be studied in controlled experiment conditions with multiple human subjects. Virtual environments are a useful tool to isolate specific human interactions for study, but current platforms support only a small scope of possible research areas. In this paper, we...

Formation control in a robot swarm targets the overall swarm shape and relative positions of individual robots during navigation. Existing approaches often use a global reference or have limited topology flexibility. We propose a novel approach without these constraints, by extending the concept of ‘mergeable nervous systems’ to establish distribut...

We present a robot swarm composed of Pi-puck robots that maintain a blockchain network. The blockchain serves as security layer to neutralize Byzantine robots (faulty, malfunctioning, or malicious robots). In the context of this work, we implemented a framework for high-throughput communication using a decentralized mobile ad-hoc network. This work...

In this paper, we carry out a review of the grey wolf, the firefly and the bat algorithms. We identify the concepts involved in these three metaphor-based algorithms and compare them to those proposed in the context of particle swarm optimization. We provide compelling evidence that the grey wolf, the firefly, and the bat algorithms are not novel,...

Consensus achievement is a crucial capability for robot swarms, for example, for path selection, spatial aggregation, or collective sensing. However, the presence of malfunctioning and malicious robots (Byzantine robots) can make it impossible to achieve consensus using classical consensus protocols. In this work, we show how a swarm of robots can...

While direct local communication is very important for the organization of robot swarms, so far it has mostly been used for relatively simple tasks such as signaling robots preferences or states. Inspired by the emergence of meaning found in natural languages, more complex communication skills could allow robot swarms to tackle novel situations in...

This book constitutes the proceedings of the 12th International Conference on Swarm Intelligence, ANTS 2020, held online -due to COVID-19- in Barcelona Spain, in October 2020. The 20 full papers presented , together with 8 short papers and 5 extended abstracts were carefully reviewed and selected from 50 submissions. ANTS 2020 contributions are dea...

In this article, we rigorously analyze the intelligent water drops (IWD) algorithm, a metaphor-based approach for the approximate solution of discrete optimization problems proposed by Shah-Hosseini (in: Proceedings of the 2007 congress on evolutionary computation (CEC 2007), IEEE Press, Piscataway, NJ, pp 3226–3231, 2007). We demonstrate that all...

We investigate the emergence of language convention within a swarm of robots foraging in an open environment from two identical resources. While foraging, the swarm needs to explore and decide which resource to exploit, moving through complex transitory dynamics towards different possible equilibria, such as, selection of a single resource or sprea...

Modern cities are growing ecosystems that face new challenges due to the increasing population demands. One of the many problems they face nowadays is waste management, which has become a pressing issue requiring new solutions. Swarm robotics systems have been attracting an increasing amount of attention in the past years and they are expected to b...

2019 IEEE. Modern cities are growing ecosystems that face new challenges due to the increasing population demands. One of the many problems they face nowadays is waste management, which has become a pressing issue requiring new solutions. Swarm robotics systems have been attracting an increasing amount of attention in the past years and they are ex...

Renewable resources like fish stock or forests should be exploited at a rate that supports regeneration and sustainability—a complex problem that requires adaptive approaches to maintain a sufficiently high exploitation while avoiding depletion. In the presence of oblivious agents that cannot keep track of all available resources—a frequent conditi...

We describe a completely open source system for performing experiments in multi-robot construction in laboratory settings. The system consists of robots that are capable of assembling cubic blocks into structures, which can be up to three blocks in height. The building material contains microcontrollers and multi-color light-emitting diodes (LEDs)...

Self-assembling robots have the potential to undergo autonomous morphological adaptation. However, due to the simplicity in their hardware makeup and their limited perspective of the environment, self-assembling robots are often not able to reach their potential and adapt their morphologies to tasks or environments without external cues or prior in...

We present an experimental study of the kinetics of orbitally-shaken, sliding macroscopic particles confined to a two-dimensional space bounded by walls. Discounting the forcing action of the external periodic actuation, the particles undergo a qualitative transition from a ballistic to a diffusive motion regime with time. Despite the deterministic...

Modern cities are growing ecosystems that face new challenges due to the increasing population demands. One of the many problems they face nowadays is waste management, which has become a pressing issue requiring new solutions. Swarm robotics systems have been attracting an increasing amount of attention in the past years and they are expected to b...

We present the Kilogrid, an open-source virtualization environment and data logging manager for the Kilobot robot, Kilobot for short. The Kilogrid has been designed to extend the sensory-motor abilities of the Kilobot, to simplify the task of collecting data during experiments, and to provide researchers with a tool to fine-control the experimental...

The indirect communication and foraging behavior of certain species of ants have inspired a number of optimization algorithms for NP-hard problems. These algorithms are nowadays collectively known as the ant colony optimization (ACO) metaheuristic. This chapter gives an overview of the history of ACO, explains in detail its algorithmic components,...

While swarm robotics systems are often claimed to be highly fault-tolerant, so far research has limited its attention to safe laboratory settings and has virtually ignored security issues in the presence of Byzantine robots-i.e., robots with arbitrarily faulty or malicious behavior. However, in many applications one or more Byzantine robots may suf...

We study the reality-gap effect (the effect of the inherent discrepancy between simulation and reality) on the human psychophysiological state, workload and reaction time in the context of a human-swarm interaction scenario. In our experiments, 37 participants perform a supervision task (i.e., the participants have to respond to visual stimuli prod...

Robots have the potential to display a higher degree of lifetime morphological adaptation than natural organisms. By adopting a modular approach, robots with different capabilities, shapes, and sizes could, in theory, construct and reconfigure themselves as required. However, current modular robots have only been able to display a limited range of...

The original version of this Article contained an error in the author contributions section, whereby credit for design of the experiments was not attributed to N.M. This error has now been corrected in both the PDF and HTML versions of the Article.

We investigate the parallel assembly of two-dimensional, geometrically-closed modular target structures out of homogeneous sets of macroscopic components of varying anisotropy. The yield predicted by a chemical reaction network (CRN)-based model is quantitatively shown to reproduce experimental results over a large set of conditions. Scaling laws f...

The ability to collectively choose the best among a finite set of alternatives is a fundamental cognitive skill for robot swarms. In this paper, we propose a formal definition of the best-of-n problem and a taxonomy that details its possible variants. Based on this taxonomy, we analyze the swarm robotics literature focusing on the decision-making p...

The reality gap is the discrepancy between simulation and reality—the same behavioural algorithm results in different robot swarm behaviours in simulation and in reality (with real robots). In this paper, we study the effect of the reality gap on the psychophysiological reactions of humans interacting with a robot swarm. We compare the psychophysio...

Designing embodied distributed systems, such as multi-robot systems, is challenging especially if the individual components have limited capabilities due to hardware restrictions. In self-organizing systems each component has only limited information and a global, organized system behavior (macro-level) has to emerge from local interactions only (m...

In order to be effective, collective decision-making strategies need to be not only fast and accurate, but sufficiently general to be ported and reused across different problem domains. In this paper, we propose a novel problem scenario, collective perception, and use it to compare three different strategies: the DMMD, DMVD, and DC strategies. The...

In this paper, we develop an autonomous construction system in which a self-contained ground robot builds a protective barrier by means of compliant pockets (i.e., filled bags). We present a stochastic control algorithm based on two biological mechanisms (stigmergy and templates) that takes advantage of compliant pockets for autonomous construction...

We study the psychophysiological state of humans when exposed to robot groups of varying sizes. In our experiments, 24 participants are exposed sequentially to groups of robots made up of 1, 3 and 24 robots. We measure both objective physiological metrics (skin conductance level and heart rate), and subjective self-reported metrics (from a psycholo...

This article investigates the use of the integral of linear birth-death processes in the context of analyzing swarm robotics systems. We show that when a robot swarm can be modeled as a linear birth-death process, well-established results can be used to compute the expected value and/or the distribution of important swarm performance measures, such...