Attractor dynamics approach to formation control : theory and application

In this paper we show how non-linear attractor dynamics can be used as a framework to control teams of autonomous mobile robots that should navigate according to a predefined geometric formation. The environment does not need to be known a priori and may change over time. Implicit to the control architecture are some important features such as establishing and moving the formation, split and join of formations (when necessary to avoid obstacles). Formations are defined by a formation matrix. By manipulating this formation matrix it is also possible to switch formations at run time. Examples of simulation results and implementations with real robots (teams of Khepera robots and medium size mobile robots), demonstrate formation switch, static and dynamic obstacle avoidance and split and join formations without the need for any explicit coordination scheme. Robustness against environmental perturbations is intrinsically achieved because the behaviour of each robot is generated as a time series of asymptotically stable states, which contribute to the asymptotic stability of the overall control system.This work was supported through COOP-DYN (POSI/SRI/38051/2001), financed by the Portuguese Foundation for Science and Technology (FCT) and project fp6-IST2 EU-project JAST-Joint Action Science and Technology (project number 003747). We thank Miguel Vaz and Nzoji Hipolito for their help in the implementations with real robots. We would like also to thank the anonymous reviewers for their insightful comments which helped improving the paper

Emergent behaviors in the Internet of things: The ultimate ultra-large-scale system

To reach its potential, the Internet of Things (IoT) must break down the silos that limit applications' interoperability and hinder their manageability. Doing so leads to the building of ultra-large-scale systems (ULSS) in several areas, including autonomous vehicles, smart cities, and smart grids. The scope of ULSS is both large and complex. Thus, the authors propose Hierarchical Emergent Behaviors (HEB), a paradigm that builds on the concepts of emergent behavior and hierarchical organization. Rather than explicitly programming all possible decisions in the vast space of ULSS scenarios, HEB relies on the emergent behaviors induced by local rules at each level of the hierarchy. The authors discuss the modifications to classical IoT architectures required by HEB, as well as the new challenges. They also illustrate the HEB concepts in reference to autonomous vehicles. This use case paves the way to the discussion of new lines of research.Damian Roca work was supported by a Doctoral Scholarship provided by Fundación La Caixa. This work has been supported by the Spanish Government (Severo Ochoa grants SEV2015-0493) and by the Spanish Ministry of Science and Innovation (contracts TIN2015-65316-P).Peer ReviewedPostprint (author's final draft

Clustering-Based Robot Navigation and Control

In robotics, it is essential to model and understand the topologies of configuration spaces in order to design provably correct motion planners. The common practice in motion planning for modelling configuration spaces requires either a global, explicit representation of a configuration space in terms of standard geometric and topological models, or an asymptotically dense collection of sample configurations connected by simple paths. In this short note, we present an overview of our recent results that utilize clustering for closing the gap between these two complementary approaches. Traditionally an unsupervised learning method, clustering offers automated tools to discover hidden intrinsic structures in generally complex-shaped and high-dimensional configuration spaces of robotic systems. We demonstrate some potential applications of such clustering tools to the problem of feedback motion planning and control. In particular, we briefly present our use of hierarchical clustering for provably correct, computationally efficient coordinated multirobot motion design, and we briefly describe how robot-centric Voronoi diagrams can be used for provably correct safe robot navigation in forest-like cluttered environments, and for provably correct collision-free coverage and congestion control of heterogeneous disk-shaped robots.For more information: Kod*la

Formation Control for a Fleet of Autonomous Ground Vehicles: A Survey

Autonomous/unmanned driving is the major state-of-the-art step that has a potential to fundamentally transform the mobility of individuals and goods. At present, most of the developments target standalone autonomous vehicles, which can sense the surroundings and control the vehicle based on this perception, with limited or no driver intervention. This paper focuses on the next step in autonomous vehicle research, which is the collaboration between autonomous vehicles, mainly vehicle formation control or vehicle platooning. To gain a deeper understanding in this area, a large number of the existing published papers have been reviewed systemically. In other words, many distributed and decentralized approaches of vehicle formation control are studied and their implementations are discussed. Finally, both technical and implementation challenges for formation control are summarized

Multilayered skill learning and movement coordination for autonomous robotic agents

With advances in technology expanding the capabilities of robots, while at the same time making robots cheaper to manufacture, robots are rapidly becoming more prevalent in both industrial and domestic settings. An increase in the number of robots, and the likely subsequent decrease in the ratio of people currently trained to directly control the robots, engenders a need for robots to be able to act autonomously. Larger numbers of robots present together provide new challenges and opportunities for developing complex autonomous robot behaviors capable of multirobot collaboration and coordination. The focus of this thesis is twofold. The first part explores applying machine learning techniques to teach simulated humanoid robots skills such as how to move or walk and manipulate objects in their environment. Learning is performed using reinforcement learning policy search methods, and layered learning methodologies are employed during the learning process in which multiple lower level skills are incrementally learned and combined with each other to develop richer higher level skills. By incrementally learning skills in layers such that new skills are learned in the presence of previously learned skills, as opposed to individually in isolation, we ensure that the learned skills will work well together and can be combined to perform complex behaviors (e.g. playing soccer). The second part of the thesis centers on developing algorithms to coordinate the movement and efforts of multiple robots working together to quickly complete tasks. These algorithms prioritize minimizing the makespan, or time for all robots to complete a task, while also attempting to avoid interference and collisions among the robots. An underlying objective of this research is to develop techniques and methodologies that allow autonomous robots to robustly interact with their environment (through skill learning) and with each other (through movement coordination) in order to perform tasks and accomplish goals asked of them. The work in this thesis is implemented and evaluated in the RoboCup 3D simulation soccer domain, and has been a key component of the UT Austin Villa team winning the RoboCup 3D simulation league world championship six out of the past seven years.Computer Science

Cyberphysical Constructs and Concepts for Fully Automated Networked Vehicles

Human lives are at stake in networked systems of automated vehicles. Drawing from mature domains where life/safety critical cyberphysical systems have already been deployed as well as from various scientific disciplines, we introduce the SPEC (Safety, Privacy, Efficiency, Cybersecurity) problem which arises in self-organizing and self-healing networks of fully automated terrestrial vehicles, and CMX functionalities intended for vehicular onboard systems. CM stands for Coordinated Mobility, X stands for S, P, E and C. The CMX framework encompasses cyberphysical constructs (cells, cohorts) endowed with proven properties, onboard proactive security modules, unfalsifiable cyberphysical levels, protocols and distributed algorithms for timed-bounded inter-vehicular communications, reliable message dissemination, trusted explicit agreements/coordination, and privacy preserving options that insulate passengers from illegitimate internal cyber-surveillance and external eavesdropping and tracking. We establish inter alia that safety and privacy can be obtained jointly, by design. The focus of this report is on SE properties. Notably, we show how to achieve theoretical absolute safety (0 fatalities and 0 severe injuries in rear-end collisions and pileups) and highest efficiency (smallest safe inter-vehicular gaps) jointly, by design, in spontaneous cohorts of vehicles. Results conveyed in this report shall open new opportunities for innovative research and development of high societal impact.Les vies humaines sont en jeu dans les réseaux de véhicules automatisés, à l’instar de domaines matures où des systèmes critiques en matière de sécurité-innocuité ont déjà été déployés. Les connaissances acquises dans ces domaines ainsi que dans diverses disciplines scientifiques permettent de définir le problème SPEC (Safety, Privacy, Efficiency, Cybersecurity) qui se pose dans les réseaux auto-organisés et auto-réparateurs de véhicules terrestres à conduite entièrement automatisée. On introduit CMX, un ensemble de fonctionnalités destinées aux systèmes bord. CM est l’abréviation de Coordinated Mobility, et X signifie S, P, E et C. L’ensemble CMX repose sur des constructions cyberphysiques (cellules, cohortes) dotées de propriétés prouvées, les concepts de module de sécurité proactif et de niveaux cyberphysiques infalsifiables, des protocoles et des algorithmes distribués pour communications inter-véhiculaires en temps borné, dissémination fiable de messages, coordination et accords explicites dignes de confiance, ainsi que sur des options de protection de la vie privée qui permettent aux passagers d’interdire la cyber-surveillance illégitime interne et externe (écoutes radio et pistage des trajets). On établit qu’il est possible de garantir conjointement sécurité-innocuité (safety) et respect de la vie privée (privacy), par conception. Ce rapport est consacré aux propriétés SE. En particulier, on montre comment obtenir la sécurité-innocuité absolue théorique (taux nul de mortalité et de graves blessures en cas de collisions longitudinales) et maximiser l’efficacité (espaces inter-véhiculaires minimaux) conjointement, par conception, dans les cohortes spontanées de véhicules. Les résultats contenus dans ce rapport devraient ouvrir de nouvelles perspectives de recherche et développement à fort impact sociétal