Supervisory Control of Robot Swarms Using Public Events

2009 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2009

This paper describes a leader-follower based formation control framework to coordinate multiple nonholonomic mobile robots. The proposed strategy deploys a control theoretic bottom-up approach where, continuous controllers are coordinated by a supervisory controlled discrete event system. All the mobile robots are required to navigate in an obstacle populated environment. And the followers keep a predetermined geometric formation with the leader while being adaptable to the constraints imposed by obstacles on the environment. The low level control is achieved by a set of behavior based controller with a high-level discrete event system that manages the dynamic interaction with the external environment. The use of discrete event systems reflects a modular manageable system with the potential for scalability and reusability. The proposed system is implemented through simulation and the results are shown to verify its operation.

2005

Abstract: It is a characteristic,of swarm,robotics that specifying overall emergent,swarm behaviours in terms,of the low-level behaviours of individual,robots is very difcult.,Yet if swarm,robotics is to make,the transition,from,the laboratory,to real-world engineering realisation,we need,such specications,. This paper,explores the use of temporal,logic to formally specify, and possibly also prove, the emergent behaviours of a robotic swarm. The paper,makes,use of a simplied,wireless connected,swarm,as a

Journal of Intelligent and Robotic Systems, 2020

The development of flexible swarm robotics systems capable of adapting to the task and environmental changes is a serious challenge. The main motivations of Swarm robotics are decentralized control, stability, adaptivity, and flexibility. Usually, ad-hoc approaches are employed to design a controller capable of meeting the problem specifications. However, these methods cannot be easily verified, and in some cases, it is not even shown that they meet the specifications. Moreover, the controller source code has to be developed separately, primarily when formal methods are employed; As a result, it cannot be guaranteed that the implementation matches the design. This paper proposes a new method-probabilistic timed supervisory control (ptSCT)-to formally design a controller from systems specifications. The proposed ptSCT has several advantages: 1) the automatic generation of the controller source code utilizable in ARGoS platform, 2) formal designing capability using the implemented software tool, 3) set of powerful design components like probabilistic decisions and time constraints, and 4) the reusability of formally designed modules among different scenarios and multiple robotic platforms. Two case studies are considered to investigate various aspects of the proposed system. Firstly, the synchronization case study is implemented for a comparison between SCT and ptSCT in terms of design capabilities and memory consumption. Secondly, the foraging case study as a complex and medium-sized problem is modeled using ptSCT step by step. More than 2400 experiments with a varying number of obstacles, targets, and robots are executed in ARGoS platform in order to show the performance of the automatically generated source code.

Lecture Notes in Computer Science, 2018

We introduce Gianduja, an automatic design method that generates communication-based behaviors for robot swarms. Gianduja extends Chocolate, a previously published design method. It does so by providing the robots with the capability to communicate using one message. The semantics of the message is not a priori fixed. It is the automatic design process that implicitly defines it, on a permission basis, by prescribing the conditions under which the message is sent by a robot and how the receiving peers react to it. We empirically study Gianduja on three missions and we compare it with the aforementioned Chocolate and with EvoCom, a rather standard evolutionary robotics method that generates communication-based behaviors. We evaluate the behaviors produced by the three automatic design methods on a swarm of 20 e-puck robots. The results show that Gianduja uses communication meaningfully and effectively in all the three missions considered. The aggregate results indicate that, on the three missions considered, Gianduja performs significantly better than the two other methods under analysis.

Given a task of designing controller for mobile robots in swarms, one might wonder which distributed control paradigms should be selected. Until now, paradigms of robot controllers have been within either behaviour based control or neural network based control, which have been recognized as two mainstreams of controller design for mobile robots. However, in swarm robotics, it is not clear how to determine control paradigms. In this paper we study the two control paradigms with various experiments of swarm aggregation. First, we introduce the two control paradigms for mobile robots. Second, we describe the physical and simulated robots, experiment scenario, and experiment setup. Third, we present our robot controllers based on behaviour based and neural network based paradigms. Fourth, we graphically show their experiment results and quantitatively analyse the results in comparison of the two methods. Closing remarks conclude the paper.

Lecture Notes in Computer Science, 2018

RoboChart is a graphical domain-specific language, based on UML, but tailored for the modelling and verification of single robot systems. In this paper, we introduce RoboChart facilities for modelling and verifying heterogeneous collections of interacting robots. We propose a new construct that describes the collection itself, and a new communication construct that allows fine-grained control over the communication patterns of the robots. Using these novel constructs, we apply RoboChart to model a simple yet powerful and widely used algorithm to maintain the aggregation of a swarm. Our constructs can be useful also in the context of other diagrammatic languages, including UML, to describe collections of arbitrary interacting entities.

2010

Tasks that require parallelism, redundancy, and adaptation to dynamic, possibly hazardous environments can potentially be performed very efficiently and robustly by a swarm robotic system. Such a system would consist of hundreds or thousands of anonymous, resource-constrained robots that operate autonomously, with little to no direct human supervision. The massive parallelism of a swarm would allow it to perform effectively in the event of robot failures, and the simplicity of individual robots facilitates a low unit cost. Key challenges in the development of swarm robotic systems include the accurate prediction of swarm behavior and the design of robot controllers that can be proven to produce a desired macroscopic outcome. The controllers should be scalable, meaning that they ensure system operation regardless of the swarm size. This thesis presents a comprehensive approach to modeling a swarm robotic system, analyzing its performance, and synthesizing scalable control policies that cause the populations of different swarm elements to evolve in a specified way that obeys time and efficiency constraints. The control policies are decentralized, computed a priori, implementable on robots with limited sensing and communication capabilities, and have theoretical guarantees on performance. To facilitate this framework of abstraction and top-down controller synthesis, the swarm is designed to emulate a system of chemically reacting molecules. The majority of this work considers well-mixed systems when there are interaction-dependent task transitions, with some modeling and analysis extensions to spatially inhomogeneous systems. The methodology is applied to the design of a swarm task allocation approach that does not rely on interrobot communication, a reconfigurable manufacturing system, and a cooperative transport strategy for groups of robots. The third application incorporates observations from a novel experimental study of the mechanics of cooperative retrieval in Aphaenogaster cockerelli ants. The correctness of the abstractions and the correspondence of the evolution of the controlled system to the target behavior are validated with computer simulations. The investigated applications form the building blocks for a versatile swarm system with integrated capabilities that have performance guarantees.

2013 American Control Conference, 2013

This paper demonstrates the application of a range of theoretical tools to generate real-time control software for multiple ground robots working together cooperatively. Specifically, existing discrete event system theory is applied to synthesize high-level supervisory control logic that is guaranteed to maintain the behavior of multiple robots within requirements defined by a set of formal specifications. The modeling of the high-level behavior of the robots in their given environment, as well as the formal specifications, is described in detail. The resulting models are represented as finite-state automata. In this work we assume that some events cannot be controlled, though all events are assumed to be observable. In addition to generating control logic that is guaranteed to keep the robots safe, results are also presented for choosing from amongst a set of allowed robot behaviors in order to achieve behavior that is "good" in some sense. Specifically, a modified version of Dijkstra's algorithm is employed to choose a path through the finite-state automaton representing the allowed robot behaviors. This modified algorithm is able to address multiple robots and the fact that some events cannot be controlled (commanded). The resulting high-level robot events are then connected to the continuous, time-driven behavior of the robots through a series of low-level algorithms. The result of this work is demonstrated in simulation for a simple, but demonstrative scenario.

2004

Coordination is an essential characteristic of any system, either natural or artificial, that is composed of multiple interacting agents. The mechanism by which the coordination is achieved determines such properties as how robust the system is to environmental perturbations, how efficient it is in performing a given task, and, more generally, what types of coordinated tasks can be achieved. A formal understanding of these issues will permit more focused analysis of coordinated natural systems and more effective approaches to the design of coordinated artificial systems. Toward this end, we are systematically investigating coordination in the context of multi-robot systems. We present a formal framework for multi-robot system (MRS) coordination and use it to discuss and reason about coordination. Using this principled foundation, we are developing a suite of general methods by which to automatically synthesize controllers for robots constituting a MRS such that a given task is performed in a coordinated fashion. This paper presents a method for the automatic synthesis of a specific type of controller, one that retains some internal state (e.g., memory of past occurrences) but is not capable of communication. Understanding the capabilities and limitations of a coordinated system composed of individual agents with such properties contributes to the understanding of when memory alone is sufficient to achieve the desired coordination and when other capabilities, such as communication, may be necessary. We validate our formal approach to the study of coordination in a multi-robot construction task domain through the use of both physically-realistic simulations and real-robot demonstrations.

2021 American Control Conference (ACC), 2021

This paper introduces a distributed leaderless swarm formation control framework to address the problem of collectively driving a swarm of robots to track a timevarying formation. The swarm's formation is captured by the trajectory of an abstract shape that circumscribes the convex hull of robots' positions and is independent of the number of robots and their ordering in the swarm. For each robot in the swarm, given global specifications in terms of the trajectory of the abstract shape parameters, the proposed framework synthesizes a control law that steers the swarm to track the desired formation using the information available at the robot's local neighbors. For this purpose, we generate a suitable local reference trajectory that the robot controller tracks by solving the input-output linearization problem. Here, we select the swarm output to be the parameters of the abstract shape. For this purpose, we design a dynamic average consensus estimator to estimate the abstract shape parameters. The abstract shape parameters are used as the swarm state feedback to generate a suitable robot trajectory. We demonstrate the effectiveness and robustness of the proposed control framework by providing the simulation of coordinated collective navigation of a group of car-like robots in the presence of robots and communication link failures.