A Survey and Analysis of Cooperative Multi-Agent Robot Systems: Challenges and Directions

Research in the area of cooperative multi-agent robot systems has received wide attention among researchers in recent years. The main concern is to find the effective coordination among autonomous agents to perform the task in order to achieve a high quality of overall performance. Therefore, this paper reviewed various selected literatures primarily from recent conference proceedings and journals related to cooperation and coordination of multi-agent robot systems (MARS). The problems, issues, and directions of MARS research have been investigated in the literature reviews. Three main elements of MARS which are the type of agents, control architectures, and communications were discussed thoroughly in the beginning of this paper. A series of problems together with the issues were analyzed and reviewed, which included centralized and decentralized control, consensus, containment, formation, task allocation, intelligences, optimization and communications of multi-agent robots. Since the research in the field of multi-agent robot research is expanding, some issues and future challenges in MARS are recalled, discussed and clarified with future directions. Finally, the paper is concluded with some recommendations with respect to multi-agent systems

Mobile Robots

The objective of this book is to cover advances of mobile robotics and related technologies applied for multi robot systems' design and development. Design of control system is a complex issue, requiring the application of information technologies to link the robots into a single network. Human robot interface becomes a demanding task, especially when we try to use sophisticated methods for brain signal processing. Generated electrophysiological signals can be used to command different devices, such as cars, wheelchair or even video games. A number of developments in navigation and path planning, including parallel programming, can be observed. Cooperative path planning, formation control of multi robotic agents, communication and distance measurement between agents are shown. Training of the mobile robot operators is very difficult task also because of several factors related to different task execution. The presented improvement is related to environment model generation based on autonomous mobile robot observations

Robust Hybrid Systems for Control, Learning, and Optimization in Networked Dynamical Systems

The deployment of advanced real-time control and optimization strategies in socially-integratedengineering systems could significantly improve our quality of life whilecreating jobs and economic opportunity. However, in cyber-physical systems such assmart grids, transportation networks, healthcare, and robotic systems, there still existseveral challenges that prevent the implementation of intelligent control strategies.These challenges include the existence of limited communication networks, dynamicand stochastic environments, multiple decision makers interacting with the system,and complex hybrid dynamics emerging from the feedback interconnection of physicalprocesses and computational devices.In this dissertation, we study the problem of designing robust control and optimizationalgorithms for cyber-physical systems using the framework of hybrid dynamicalsystems. We propose different theoretical frameworks for the design and analysis offeedback mechanisms that optimize the performance of dynamical systems without requiringan explicit characterization of their mathematical model, i.e., in a model-freeway. The closed-loop system that emerges of the interconnection of the plant with thefeedback mechanism describes, in general, a set-valued hybrid dynamical system. Thesetypes of systems combine continuous-time and discrete-time dynamics, and they usuallylack the uniqueness of solutions property. The framework of set-valued hybriddynamical systems allows us to study many complex dynamical systems that emerge indifferent engineering applications, such as networked multi-agent systems with switching graphs, non-smooth mechanical systems, dynamic pricing mechanisms in transportationsystems, autonomous robots with logic-based controllers, etc. We proposea step-by-step approach to the design of different types of discrete-time, continuous-time,hybrid, and stochastic controllers for different types of applications, extendingand generalizing different results in the literature in the area of extremum seeking control,sampled-data extremization, robust synchronization, and stochastic learning innetworked systems. Our theoretical results are illustrated via different simulations andnumerical examples

Cyber-Human Systems, Space Technologies, and Threats

CYBER-HUMAN SYSTEMS, SPACE TECHNOLOGIES, AND THREATS is our eighth textbook in a series covering the world of UASs / CUAS/ UUVs / SPACE. Other textbooks in our series are Space Systems Emerging Technologies and Operations; Drone Delivery of CBNRECy – DEW Weapons: Emerging Threats of Mini-Weapons of Mass Destruction and Disruption (WMDD); Disruptive Technologies with applications in Airline, Marine, Defense Industries; Unmanned Vehicle Systems & Operations On Air, Sea, Land; Counter Unmanned Aircraft Systems Technologies and Operations; Unmanned Aircraft Systems in the Cyber Domain: Protecting USA’s Advanced Air Assets, 2nd edition; and Unmanned Aircraft Systems (UAS) in the Cyber Domain Protecting USA’s Advanced Air Assets, 1st edition. Our previous seven titles have received considerable global recognition in the field. (Nichols & Carter, 2022) (Nichols, et al., 2021) (Nichols R. K., et al., 2020) (Nichols R. , et al., 2020) (Nichols R. , et al., 2019) (Nichols R. K., 2018) (Nichols R. K., et al., 2022)https://newprairiepress.org/ebooks/1052/thumbnail.jp

Virtual Reality Games for Motor Rehabilitation

This paper presents a fuzzy logic based method to track user satisfaction without the need for devices to monitor users physiological conditions. User satisfaction is the key to any product’s acceptance; computer applications and video games provide a unique opportunity to provide a tailored environment for each user to better suit their needs. We have implemented a non-adaptive fuzzy logic model of emotion, based on the emotional component of the Fuzzy Logic Adaptive Model of Emotion (FLAME) proposed by El-Nasr, to estimate player emotion in UnrealTournament 2004. In this paper we describe the implementation of this system and present the results of one of several play tests. Our research contradicts the current literature that suggests physiological measurements are needed. We show that it is possible to use a software only method to estimate user emotion

Emerging Threats of Synthetic Biology and Biotechnology

Synthetic biology is a field of biotechnology that is rapidly growing in various applications, such as in medicine, environmental sustainability, and energy production. However these technologies also have unforeseen risks and applications to humans and the environment. This open access book presents discussions on risks and mitigation strategies for these technologies including biosecurity, or the potential of synthetic biology technologies and processes to be deliberately misused for nefarious purposes. The book presents strategies to prevent, mitigate, and recover from ‘dual-use concern’ biosecurity challenges that may be raised by individuals, rogue states, or non-state actors. Several key topics are explored including opportunities to develop more coherent and scalable approaches to govern biosecurity from a laboratory perspective up to the international scale and strategies to prevent potential health and environmental hazards posed by deliberate misuse of synthetic biology without stifling innovation. The book brings together the expertise of top scholars in synthetic biology and biotechnology risk assessment, management, and communication to discuss potential biosecurity governing strategies and offer perspectives for collaboration in oversight and future regulatory guidance

Estimation and stability of nonlinear control systems under intermittent information with applications to multi-agent robotics

This dissertation investigates the role of intermittent information in estimation and control problems and applies the obtained results to multi-agent tasks in robotics. First, we develop a stochastic hybrid model of mobile networks able to capture a large variety of heterogeneous multi-agent problems and phenomena. This model is applied to a case study where a heterogeneous mobile sensor network cooperatively detects and tracks mobile targets based on intermittent observations. When these observations form a satisfactory target trajectory, a mobile sensor is switched to the pursuit mode and deployed to capture the target. The cost of operating the sensors is determined from the geometric properties of the network, environment and probability of target detection. The above case study is motivated by the Marco Polo game played by children in swimming pools. Second, we develop adaptive sampling of targets positions in order to minimize energy consumption, while satisfying performance guarantees such as increased probability of detection over time, and no-escape conditions. A parsimonious predictor-corrector tracking filter, that uses geometrical properties of targets\u27 tracks to estimate their positions using imperfect and intermittent measurements, is presented. It is shown that this filter requires substantially less information and processing power than the Unscented Kalman Filter and Sampling Importance Resampling Particle Filter, while providing comparable estimation performance in the presence of intermittent information. Third, we investigate stability of nonlinear control systems under intermittent information. We replace the traditional periodic paradigm, where the up-to-date information is transmitted and control laws are executed in a periodic fashion, with the event-triggered paradigm. Building on the small gain theorem, we develop input-output triggered control algorithms yielding stable closed-loop systems. In other words, based on the currently available (but outdated) measurements of the outputs and external inputs of a plant, a mechanism triggering when to obtain new measurements and update the control inputs is provided. Depending on the noise environment, the developed algorithm yields stable, asymptotically stable, and Lp-stable (with bias) closed-loop systems. Control loops are modeled as interconnections of hybrid systems for which novel results on Lp-stability are presented. Prediction of a triggering event is achieved by employing Lp-gains over a finite horizon in the small gain theorem. By resorting to convex programming, a method to compute Lp-gains over a finite horizon is devised. Next, we investigate optimal intermittent feedback for nonlinear control systems. Using the currently available measurements from a plant, we develop a methodology that outputs when to update the control law with new measurements such that a given cost function is minimized. Our cost function captures trade-offs between the performance and energy consumption of the control system. The optimization problem is formulated as a Dynamic Programming problem, and Approximate Dynamic Programming is employed to solve it. Instead of advocating a particular approximation architecture for Approximate Dynamic Programming, we formulate properties that successful approximation architectures satisfy. In addition, we consider problems with partially observable states, and propose Particle Filtering to deal with partially observable states and intermittent feedback. Finally, we investigate a decentralized output synchronization problem of heterogeneous linear systems. We develop a self-triggered output broadcasting policy for the interconnected systems. Broadcasting time instants adapt to the current communication topology. For a fixed topology, our broadcasting policy yields global exponential output synchronization, and Lp-stable output synchronization in the presence of disturbances. Employing a converse Lyapunov theorem for impulsive systems, we provide an average dwell time condition that yields disturbance-to-state stable output synchronization in case of switching topology. Our approach is applicable to directed and unbalanced communication topologies.\u2

European governance challenges in bio-engineering : making perfect life : bio-engineering (in) the 21st century : final report

In the STOA project Making Perfect Life four fields were studied of 21st century bio-engineering: engineering of living artefacts, engineering of the body, engineering of the brain, and engineering of intelligent artefacts. This report describes the main results of the project. It shows how developments in the four fields of bio-engineering are shaped by two megatrends: "biology becoming technology" and "technology becoming biology". These developments result in a broadening of the bio-engineering debate in our society. The report addresses the long term views that are inspiring this debate and discusses a multitude of ethical, legal and social issues that arise from bio-engineering developments in the fields described. Against this background four specific developments are studied in more detail: the rise of human genome sequencing, the market introduction of neurodevices, the capturing by information technology of the psychological and physiological states of users, and the pursuit of standardisation in synthetic biology. These developments are taken in this report as a starting point for an analysis of some of the main European governance challenges in 21st century bio-engineering

European governance challenges in bio-engineering : making perfect life : bio-engineering (in) the 21st century : final report

In the STOA project Making Perfect Life four fields were studied of 21st century bio-engineering: engineering of living artefacts, engineering of the body, engineering of the brain, and engineering of intelligent artefacts. This report describes the main results of the project. It shows how developments in the four fields of bio-engineering are shaped by two megatrends: "biology becoming technology" and "technology becoming biology". These developments result in a broadening of the bio-engineering debate in our society. The report addresses the long term views that are inspiring this debate and discusses a multitude of ethical, legal and social issues that arise from bio-engineering developments in the fields described. Against this background four specific developments are studied in more detail: the rise of human genome sequencing, the market introduction of neurodevices, the capturing by information technology of the psychological and physiological states of users, and the pursuit of standardisation in synthetic biology. These developments are taken in this report as a starting point for an analysis of some of the main European governance challenges in 21st century bio-engineering

Dissociation and interpersonal autonomic physiology in psychotherapy research: an integrative view encompassing psychodynamic and neuroscience theoretical frameworks

Interpersonal autonomic physiology is an interdisciplinary research field, assessing the relational interdependence of two (or more) interacting individual both at the behavioral and psychophysiological levels. Despite its quite long tradition, only eight studies since 1955 have focused on the interaction of psychotherapy dyads, and none of them have focused on the shared processual level, assessing dynamic phenomena such as dissociation. We longitudinally observed two brief psychodynamic psychotherapies, entirely audio and video-recorded (16 sessions, weekly frequency, 45 min.). Autonomic nervous system measures were continuously collected during each session. Personality, empathy, dissociative features and clinical progress measures were collected prior and post therapy, and after each clinical session. Two-independent judges, trained psychotherapist, codified the interactions\u2019 micro-processes. Time-series based analyses were performed to assess interpersonal synchronization and de-synchronization in patient\u2019s and therapist\u2019s physiological activity. Psychophysiological synchrony revealed a clear association with empathic attunement, while desynchronization phases (range of length 30-150 sec.) showed a linkage with dissociative processes, usually associated to the patient\u2019s narrative core relational trauma. Our findings are discussed under the perspective of psychodynamic models of Stern (\u201cpresent moment\u201d), Sander, Beebe and Lachmann (dyad system model of interaction), Lanius (Trauma model), and the neuroscientific frameworks proposed by Thayer (neurovisceral integration model), and Porges (polyvagal theory). The collected data allows to attempt an integration of these theoretical approaches under the light of Complex Dynamic Systems. The rich theoretical work and the encouraging clinical results might represents a new fascinating frontier of research in psychotherapy