Abstract:

Swarm robotics studies large groups of robots that work together to accomplish common tasks. Much of the used source code is developed in an ad-hoc manner, meaning that the correctness of the controller is not always verifiable. In previous work, supervisory control theory (SCT) and associated design tools have been used to address this problem. Given a formal description of the swarm’s agents capabilities and their desired behaviour, the control source code can be automatically generated. However, regular SCT cannot model probabilistic controllers (supervisors). In this paper, we propose a probabilistic supervisory control theory (pSCT) framework. It applies prior work on probabilistic generators in a way that allows controllers to be decomposed into multiple local modular supervisors. Local modular supervisors take advantage of the modularity of formal specifications to reduce the size required to store the control logic. To validate the pSCT framework, we model a distributed swarm robotic version of the graph colouring problem and automatically generate the control source code for the Kilobot swarm robotics platform. We report the results of systematic experiments with swarms of 25 and 100 physical robots.

Abstract:

This paper presents OpenSwarm, a lightweight, easy-to-use open-source operating system. To our knowledge, it is the first operating system designed for and deployed on miniature robots. OpenSwarm operates directly on a robot’s microcontroller. It has a memory footprint of 1 kB RAM and 12 kB ROM. OpenSwarm enables a robot to execute multiple processes simultaneously. It provides a hybrid kernel that natively supports preemptive and cooperative scheduling, making it suitable for both computationally intensive and swiftly responsive robotics tasks. OpenSwarm provides hardware abstractions to rapidly develop and test platform-independent code. We show how OpenSwarm can be used to solve a canonical problem in swarm robotics—clustering a collection of dispersed objects. We report experiments, conducted with five e-puck mobile robots, that show that an OpenSwarm implementation performs as good as a hardware-near implementation. The primary goal of OpenSwarm is to make robots with severely constrained hardware more accessible, which may help such systems to be deployed in real-world applications.

Abstract:

Synchronization can be a key requirement to perform coordinated actions or reach consensus in multi-robot systems. We study the effect of robot speed on the time required to achieve synchronization using pulse coupled oscillators. Each robot has an internal oscillator and the completion of oscillation cycles is signaled by means of short visual pulses. These can, in turn, be detected by other robots within their cone of vision. In this way, oscillators influence each other to attain temporal synchrony. We observe in simulation and in physical robotic experiments that synchronization can be fostered or inhibited by tuning the robot speed, leading to distinct dynamical regimes. In addition, we analyze the effect of the involved parameters on the time it takes for the system to synchronize.

Abstract:
Supervisory Control Theory (SCT) provides a formal framework for controlling discrete event systems. It has recently been used to generate correct-by-construction controllers for swarm robotics systems. Current SCT frameworks are limited, as they support only (private) events that are observable within the same robot. In this paper, we propose an extended SCT framework that incorporates (public) events that are shared among robots. The extended framework allows formal modelling of the interactions among the robots. It is evaluated using a case study, where a group of mobile robots need to synchronise their movements in space and time—a requirement that is specified at the formal level. We validate our approach through experiments with groups of e-puck robots.

Abstract:

When it comes to describing robots, many roboticists choose to focus on the size, types of actuators or other physical capabilities. As most areas of robotics deploy robots with large memory and processing power, the question “how computational resources limit what a robot can do” is often overlooked.
However, the capabilities of many miniature robots are limited by significantly less memory and processing power. At present, there is no systematic approach to comparing and quantifying the computational resources as a whole and their implications.
This paper proposes computational indices that systematically quantify computational resources—individually and as a whole. Then, by comparing 31 state-of-the-art miniature robots, a computational classification ranging from non-computing to minimally-constrained robots is introduced. Finally, the implications of computational constraints on robotic software are discussed.

Abstract

Abstract:

Abstract:

Swarm robotics is a relatively new and multidisciplinary research field with many potential applications (e.g., collective exploration or precision agriculture). Nevertheless, it has not been able to transition from the academic environment to the real world. While there are many potential reasons, one reason is that many robots are designed to be relatively simple, which often results in reduced communication and computation capabilities. However, the investigation of such limitations has largely been overlooked.

This thesis looks into one such constraint, the computational constraint of swarm robots (i.e., swarm robotics platform). To achieve this, this work first proposes a computational index that quantifies computational resources. Based on the computational index, a quantitative study of 5273 devices shows that swarm robots provide fewer resources than many other robots or devices. In the next step, an operating system with a novel dual-execution model is proposed, and it has been shown that it outperforms the two other robotic system software. Moreover, results show that the choice of system software determines the computational overhead and, therefore, how many resources are available to robotic software. As communication can be a key aspect of a robot’s behaviour, this work demonstrates the modelling, implementing, and studying of an optical communication system with a novel dynamic detector. Its detector improves the quality of service by orders of magnitude (i.e., makes the communication more reliable). In addition, this work investigates general communication properties, such as scalability or the effects of mobility, and provides recommendations for the use of such optical communication systems for swarm robotics. Finally, an approach is shown by which computational constraints of individual robots can be overcome by distributing data and processing across multiple robots.