Heiko Hamann

University of Konstanz | Uni-Konstanz · Department of Computer and Information Science

This book provides an introduction to Swarm Robotics, which is the application of methods from swarm intelligence to robotics. It goes on to present methods that allow readers to understand how to design large-scale robot systems by going through many example scenarios on topics such as aggregation, coordinated motion (flocking), task allocation, s...

The physiology of living organisms, such as living plants, is complex and particularly difficult to understand on a macroscopic, organism-holistic level. Among the many options to study plant physiology, electrical potential and tissue impedance are arguably simple measurement techniques to gather plant-level information. Despite the many possible...

Natural and artificial collectives exhibit heterogeneities across different dimensions, contributing to the complexity of their behavior. We investigate the effect of two such heterogeneities on collective opinion dynamics: heterogeneity of the quality of agents’ prior information and of degree centrality in the network. To study these heterogeneit...

Swarm intelligence (SI) explores how large groups of simple individuals (e.g., insects, fish, birds) collaborate to produce complex behaviors, exemplifying that the whole is greater than the sum of its parts. A fundamental task in SI is Collective Decision-Making (CDM), where a group selects the best option among several alternatives, such as choos...

We present the Light Augmented Reality System LARS as an open-source and cost-effective tool. LARS leverages light-projected visual scenes for indirect robot-robot and human-robot interaction through the real environment. It operates in real-time and is compatible with a range of robotic platforms, from miniature to middle-sized robots. LARS can su...

Collective movement inspired by animal groups promises inherited benefits for robot swarms, such as enhanced sensing and efficiency. However, while animals move in groups using only their local senses, robots often obey central control or use direct communication, introducing systemic weaknesses to the swarm. In the hope of addressing such vulnerab...

Collective estimation manifests computational intelligence emerging from inter-individual local interactions, e.g., by aggregating opinions from neighbors to estimate a quantity. Use cases of collective estimation may include directed motion in physical space, such that agents, for example, have to collectively explore a distributed feature, and co...

One of the most important promises of decentralized systems is scalability, which is often assumed to be present in robot swarm systems without being contested. Simple limitations, such as movement congestion and communication conflicts, can drastically affect scalability. In this work, we study the effects of congestion in a binary collective deci...

Preprint available on arXiv: https://arxiv.org/abs/2311.02994

Collective decision-making is an essential capability of large-scale multi-robot systems to establish autonomy on the swarm level. A large portion of literature on collective decision-making in swarm robotics focuses on discrete decisions selecting from a limited number of options. Here we assign a decentralized robot system with the task of explor...

Inter-individual differences are studied in natural systems, such as fish, bees, and humans, as they contribute to the complexity of both individual and collective behaviors. However, individuality in artificial systems, such as robotic swarms, is undervalued or even overlooked. Agent-specific deviations from the norm in swarm robotics are usually...

Collective decision-making is an essential capability of large-scale multi-robot systems to establish autonomy on the swarm level. A large portion of literature on collective decision-making in swarm robotics focuses on discrete decisions selecting from a limited number of options. Here we assign a decentralized robot system with the task of explor...

Applications of large-scale mobile multirobot systems can be beneficial over monolithic robots because of higher potential for robustness and scalability. Developing controllers for multirobot systems is challenging because the multitude of interactions is hard to anticipate and difficult to model. Automatic design using machine learning or evoluti...

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...

Cities worldwide are growing, putting bigger populations at risk due to urban pollution. Environmental monitoring is essential and requires a major paradigm shift. We need green and inexpensive means of measuring at high sensor densities and with high user acceptance. We propose using phytosensing: using natural living plants as sensors. In plant e...

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...

Developing reusable software for mobile robots is still challenging. Even more so for swarm robots, despite the desired simplicity of the robot controllers. Prototyping and experimenting are difficult due to the multi-robot setting and often require robot-robot communication. Also, the diversity of swarm robot hardware platforms increases the need...

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...

Pedestrians are particularly vulnerable road users in urban traffic. With the arrival of autonomous driving, novel technologies can be developed specifically to protect pedestrians. We propose a~machine learning toolchain to train artificial neural networks as models of pedestrian behavior. In a~preliminary study, we use synthetic data from simulat...

The tradeoff between accuracy and speed is considered fundamental to individual and collective decision-making. In this paper, we focus on collective estimation as an example of collective decision-making. The task is to estimate the average scalar intensity of a desired feature in the environment. The solution we propose consists of exploration an...

As our contribution to the effort of developing methods to make robots more adaptive and robust to dynamic environments, we have proposed our method of ‘minimal surprise’ in a series of previous works. In a multi-robot setting, we use evolutionary computation to evolve pairs of artificial neural networks: an actor network to select motor speeds and...

The tradeoff between accuracy and speed is considered fundamental to individual and collective decision-making. In this paper, we focus on collective estimation as an example of collective decision-making. The task is to estimate the average scalar intensity of a desired feature in the environment. The solution we propose consists of exploration an...

Controlling large-scale particle or robot systems is challenging because of their high dimensionality. We use a centralized stochastic approach that allows for optimal control at the cost of a central element instead of a decentralized approach. Previous works are often restricted to the assumption of fully actuated robots. Here we propose an appro...

A scalable system has increasing performance with increasing system size. Coordination among units can introduce overheads with an impact on system performance. The coordination costs can lead to sublinear improvement or even diminishing performance with increasing system size. However, there are also systems that implement efficient coordination a...

In evolutionary robotics, an encoding of the control software that maps sensor data (input) to motor control values (output) is shaped by stochastic optimization methods to complete a predefined task. This approach is assumed to be beneficial compared to standard methods of controller design in those cases where no a priori model is available that...

Scalability is a key feature of swarm robotics. Hence, measuring performance depending on swarm size is important to check the validity of the design. Performance diagrams have generic qualities across many different application scenarios. We summarize these findings and condense them in a practical performance analysis guide for swarm robotics. We...

Efficient engineered systems require scalability. A scalable system has increasing performance with increasing system size. In an ideal case, the increase in performance (e.g., speedup) corresponds to the number of units that are added to the system. However, if multiple units work on the same task, then coordination among these units is required....

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 software engineering, the imprecise requirements of a user are transformed to a formal requirements specification during the requirements elicitation process. This process is usually guided by requirements engineers interviewing the user. We want to partially automate this first step of the software engineering process in order to enable users t...

Using multi-robot systems for autonomous construction allows for parallelization and scalability. In swarm construction we tend to go one step further as we exploit intensive robot interactions and collaboration such that the robot swarm collectively constructs artifacts beyond what a single robot could achieve. Here we present an alternative conce...

Applying principles of swarm intelligence to the control of autonomous systems in industry can advance our ability to manage complexity in prominent and high-cost sectors—such as transportation, logistics, and construction. In swarm robotics, the exclusive use of decentralized control relying on local communication and information provides the key...

In collective robotic systems, the automatic generation of controllers for complex tasks is still a challenging problem. Open-ended evolution of complex robot behaviors can be a possible solution whereby an intrinsic driver for pattern formation and self-organization may prove to be important. We implement such a driver in collective robot systems...

Robot swarms are known to be robust to individual robot failures. However, a reduced swarm size causes a reduced swarm density. A too low swarm density may then decrease swarm performance, that should be compensated by adapting the individual behavior. Similarly, swarm behaviors can also be adapted to changes in the environment, such as dynamic lig...

Biohybrid robotics takes an engineering approach to the expansion and exploitation of biological behaviors for application to automated tasks. Here we identify the construction of living buildings and infrastructure as a high-potential application domain for biohybrid robotics, and review technological advances relevant to its future development. C...

Zu Beginn definieren wir wichtige Begriffe zur Beschreibung des Verhaltens von Tieren, Software-Agenten und Robotern. Dann lernen wir einige Beispiele von Verhalten bei sozialen Insekten kennen. Abschließend überlegen wir, ob auch manche menschlichen Verhaltensweisen mit dem Begriff der Schwarmintelligenz beschrieben oder erklärt werden können.

Entscheiden zu handeln , ob allein oder in der Gruppe, ist elementar für Einzeltiere und Schwärme. Nach einer kurzen Einführung in die Grundlagen des Entscheidens, gehen wir eine Vielzahl an Modellen durch. Die Modelle kommen dabei ursprünglich aus ganz verschiedenen Bereichen, etwa der Physik oder der Meinungsdynamik.

Wir erfahren, was Schwärme und Schwarmverhalten sind und definieren den elementaren Begriff der Selbstorganisation. Wie es funktioniert, dass sich viele Tiere oder Agenten in einem Schwarm effizient koordinieren, untersuchen wir anhand des Begriffs der Skalierbarkeit.

In diesem Kapitel gehen wir einige Beispiele von Schwarmverhalten in biologischen und ingenieurtechnischen Systemen durch. Die Vielfalt ist potenziell groß, wir beschränken uns hier auf ein paar repräsentative Beispiele. Die Szenarien sind grob nach Komplexität geordnet.

Wir erfahren, was bei der Modellierung von Schwarmsystemen besonders ist. Mit den Ratengleichungen und speziellen Differentialgleichungen für die räumliche Modellierung lernen wir zwei Techniken kennen. Abschließend lernen wir, wie man Schwarmverhalten mittels der Definition für Selbstorganisation erkennen und automatisch erzeugen kann.

Self-assembly in biology is an inspiration for engineered large-scale multi-modular systems with desirable characteristics, such as robustness, scalability, and adaptivity. Previous works have shown that simple mobile robots can be used to emulate and study self-assembly behaviors. However, many of these studies were restricted to rather static and...

Robot systems are actively researched for manipulation of natural plants, typically restricted to agricultural automation activities such as harvest, irrigation, and mechanical weed control. Extending this research, we introduce here a novel methodology to manipulate the directional growth of plants via their natural mechanisms for signaling and ho...

In a collaborative society, sharing information is advantageous for each individual as well as for the whole community. Maximizing the number of agent-to-agent interactions per time becomes an appealing behavior due to fast information spreading that maximizes the overall amount of shared information. However, if malicious agents are part of societ...

Video and full text available here: https://dx.doi.org/10.3791/59835-v

The workshop on self-organised construction aims at cumulating, presenting, discussing and advancing new research results from theory and practice as well as novel scientific concepts and methodologies. Originally inspired by nest construction in social insects, the general concept relies on a large number of agents that coordinate their constructi...

Autonomous decision-making is a fundamental requirement for the intelligent behavior of individual agents and systems. For artificial systems, one of the key design prerequisites is providing the system with the ability to make proper decisions. Current literature on collective artificial systems designs decision-making mechanisms inspired mostly b...

In collective robotic systems, the automatic generation of controllers for complex tasks is still a challenging problem. Open-ended evolution of complex robot behaviors can be a possible solution whereby an intrinsic driver for pattern formation and self-organization may prove to be important. We implement such a driver in collective robot systems...

For self-assembly, robot swarms can be programmed to form predefined shapes. However, if the swarm is required to adapt the assembled shapes to dynamic features of the environment at runtime, then the shapes’ structures need to be dynamic, too. A prerequisite for adaptation is the exploration and detection of changes followed by appropriate rearran...

Dieses Buch führt den Leser schnell und präzise in die Grundprinzipien der Schwarmintelligenz ein, geleitet von der Frage: Wie können große Gruppen von Tieren, Robotern oder Menschen gemeinsam Ziele erreichen? Die Wirkmechanismen der Schwarmintelligenz und der effizienten Zusammenarbeit, wie Selbstorganisation und Skalierbarkeit, werden eingehend b...

Over the past few years, robots have found their way to the consumer market. With the rise of ubiquitous digitization, the transformative potential of robotics is immense. Yet, it is important to educate a new generation of robotics engineers on researching and engineering mobile robots and also multi-robot systems. Often, students' great intrinsic...

Plant growth is a self-organized process incorporating distributed sensing, internal communication and morphology dynamics. We develop a distributed mechatronic system that autonomously interacts with natural climbing plants, steering their behaviours to grow user-defined shapes and patterns. Investigating this bio-hybrid system paves the way towar...

For self-assembly, robot swarms can be programmed to form predefined shapes. However, if the swarm is required to adapt the assembled shapes to dynamic features of the environment at runtime, then the shapes' structures need to be dynamic, too. A prerequisite for adaptation is the exploration and detection of changes followed by appropriate rearran...

Self-assembly is the aggregation of simple parts into complex patterns as frequently observed in nature. Following this inspiration, creating programmable systems of self-assembly that achieve similar complexity and robustness with robots is challenging. As a role model we pick the growth of natural plants that adapts to environmental conditions an...

Bio-hybrid systems---close couplings of natural organisms with technology---are high potential and still underexplored. In existing work, robots have mostly influenced group behaviors of animals. We explore the possibilities of mixing robots with natural plants, merging useful attributes. Significant synergies arise by combining the plants' ability...

We investigate the dynamics of opinion formation in a group of mobile agents with noisy perceptions. Two models are applied, the 2-state Galam opinion dynamics model with contrarians and an urn model of collective decision-making. It is shown that models built on the well-mixed assumption fail to represent the dynamics of a simple scenario. The cha...