1,011 research outputs found
A Survey and Analysis of Multi-Robot Coordination
International audienceIn the field of mobile robotics, the study of multi-robot systems (MRSs) has grown significantly in size and importance in recent years. Having made great progress in the development of the basic problems concerning single-robot control, many researchers shifted their focus to the study of multi-robot coordination. This paper presents a systematic survey and analysis of the existing literature on coordination, especially in multiple mobile robot systems (MMRSs). A series of related problems have been reviewed, which include a communication mechanism, a planning strategy and a decision-making structure. A brief conclusion and further research perspectives are given at the end of the paper
Analysis and Control of Mobile Robots in Various Environmental Conditions
The world sees new inventions each day, made to make the lifestyle of humans more easy and luxurious. In such global scenario, the robots have proved themselves to be an invention of great importance. The robots are being used in almost each and every field of the human world. Continuous studies are being done on them to make them simpler and easier to work with. All fields are being unraveled to make them work better in the human world without human interference. We focus on the navigation field of these mobile robots. The aim of this thesis is to find the controller that produces the most optimal path for the robot to reach its destination without colliding or damaging itself or the environment. The techniques like Fuzzy logic, Type 2 fuzzy logic, Neural networks and Artificial bee colony have been discussed and experimented to find the best controller that could find the most optimal path for the robot to reach its goal position. Simulation and Experiments have been done alike to find out the optimal path for the robot
Navigational Path Analysis of Mobile Robot in Various Environments
This dissertation describes work in the area of an autonomous mobile robot. The objective is navigation of mobile robot in a real world dynamic environment avoiding structured and unstructured obstacles either they are static or dynamic. The shapes and position of obstacles are not known to robot prior to navigation. The mobile robot has sensory recognition of specific objects in the environments. This sensory-information provides local information of robots immediate surroundings to its controllers. The information is dealt intelligently by the robot to reach the global objective (the target). Navigational paths as well as time taken during navigation by the mobile robot can be expressed as an optimisation problem and thus can be analyzed and solved using AI techniques. The optimisation of path as well as time taken is based on the kinematic stability and the intelligence of the robot controller. A successful way of structuring the navigation task deals with the issues of individual behaviour design and action coordination of the behaviours. The navigation objective is addressed using fuzzy logic, neural network, adaptive neuro-fuzzy inference system and different other AI technique.The research also addresses distributed autonomous systems using multiple robot
Machine Learning-Aided Operations and Communications of Unmanned Aerial Vehicles: A Contemporary Survey
The ongoing amalgamation of UAV and ML techniques is creating a significant
synergy and empowering UAVs with unprecedented intelligence and autonomy. This
survey aims to provide a timely and comprehensive overview of ML techniques
used in UAV operations and communications and identify the potential growth
areas and research gaps. We emphasise the four key components of UAV operations
and communications to which ML can significantly contribute, namely, perception
and feature extraction, feature interpretation and regeneration, trajectory and
mission planning, and aerodynamic control and operation. We classify the latest
popular ML tools based on their applications to the four components and conduct
gap analyses. This survey also takes a step forward by pointing out significant
challenges in the upcoming realm of ML-aided automated UAV operations and
communications. It is revealed that different ML techniques dominate the
applications to the four key modules of UAV operations and communications.
While there is an increasing trend of cross-module designs, little effort has
been devoted to an end-to-end ML framework, from perception and feature
extraction to aerodynamic control and operation. It is also unveiled that the
reliability and trust of ML in UAV operations and applications require
significant attention before full automation of UAVs and potential cooperation
between UAVs and humans come to fruition.Comment: 36 pages, 304 references, 19 Figure
A generic architecture style for self-adaptive cyber-physical systems
Die aktuellen Konzepte zur Gestaltung von Regelungssystemen basieren auf dynamischen
Verhaltensmodellen, die mathematische Ansätze wie Differentialgleichungen zur Ableitung der
entsprechenden Funktionen verwenden. Diese Konzepte stoßen jedoch aufgrund der zunehmenden
Systemkomplexität allmählich an ihre Grenzen. Zusammen mit der Entwicklung dieser Konzepte
entsteht eine Architekturevolution der Regelungssysteme.
In dieser Dissertation wird eine Taxonomie definiert, um die genannte Architekturevolution anhand
eines typischen Beispiels, der adaptiven Geschwindigkeitsregelung (ACC), zu veranschaulichen.
Aktuelle ACC-Varianten, die auf der Regelungstheorie basieren, werden in Bezug auf ihre Architekturen
analysiert. Die Analyseergebnisse zeigen, dass das zukünftige Regelungssystem im ACC eine
umfangreichere Selbstadaptationsfähigkeit und Skalierbarkeit erfordert. Dafür sind kompliziertere
Algorithmen mit unterschiedlichen Berechnungsmechanismen erforderlich. Somit wird die
Systemkomplexität erhöht und führt dazu, dass das zukünftige Regelungssystem zu einem
selbstadaptiven cyber-physischen System wird und signifikante Herausforderungen für die
Architekturgestaltung des Systems darstellt.
Inspiriert durch Ansätze des Software-Engineering zur Gestaltung von Architekturen von
softwareintensiven Systemen wird in dieser Dissertation ein generischer Architekturstil entwickelt. Der
entwickelte Architekturstil dient als Vorlage, um vernetzte Architekturen mit Verfolgung der
entwickelten Designprinzipien nicht nur für die aktuellen Regelungssysteme, sondern auch für
selbstadaptiven cyber-physischen Systeme in der Zukunft zu konstruieren. Unterschiedliche
Auslösemechanismen und Kommunikationsparadigmen zur Gestaltung der dynamischen Verhalten
von Komponenten sind in der vernetzten Architektur anwendbar.
Zur Bewertung der Realisierbarkeit des Architekturstils werden aktuelle ACCs erneut aufgenommen,
um entsprechende logische Architekturen abzuleiten und die Architekturkonsistenz im Vergleich zu
den originalen Architekturen basierend auf der Regelungstheorie (z. B. in Form von Blockdiagrammen)
zu untersuchen. Durch die Anwendung des entwickelten generischen Architekturstils wird in dieser
Dissertation eine künstliche kognitive Geschwindigkeitsregelung (ACCC) als zukünftige ACC-Variante
entworfen, implementiert und evaluiert. Die Evaluationsergebnisse zeigen signifikante
Leistungsverbesserungen des ACCC im Vergleich zum menschlichen Fahrer und aktuellen ACC-Varianten.Current concepts of designing automatic control systems rely on dynamic behavioral
modeling by using mathematical approaches like differential equations to
derive corresponding functions, and slowly reach limitations due to increasing
system complexity. Along with the development of these concepts, an
architectural evolution of automatic control systems is raised.
This dissertation defines a taxonomy to illustrate the aforementioned architectural
evolution relying on a typical example of control application: adaptive cruise control
(ACC). Current ACC variants, with their architectures considering control theory, are
analyzed. The analysis results indicate that the future automatic control system in ACC
requires more substantial self-adaptation capability and scalability. For this purpose,
more complicated algorithms requiring different computation mechanisms must be
integrated into the system and further increase system complexity. This makes the future
automatic control system evolve into a self-adaptive cyber-physical system and
consistitutes significant challenges for the system’s architecture design.
Inspired by software engineering approaches for designing architectures of software-intensive systems, a generic architecture style is proposed. The proposed architecture
style serves as a template by following the developed design principle to construct
networked architectures not only for the current automatic control systems but also for
self-adaptive cyber-physical systems in the future. Different triggering mechanisms and
communication paradigms for designing dynamic behaviors are applicable in the
networked architecture.
To evaluate feasibility of the architecture style, current ACCs are retaken to derive
corresponding logical architectures and examine architectural consistency compared to
the previous architectures considering the control theory (e.g., in the form of block
diagrams). By applying the proposed generic architecture style, an artificial cognitive
cruise control (ACCC) is designed, implemented, and evaluated as a future ACC in this
dissertation. The evaluation results show significant performance improvements in the
ACCC compared to the human driver and current ACC variants
Multi-Agent Systems
A multi-agent system (MAS) is a system composed of multiple interacting intelligent agents. Multi-agent systems can be used to solve problems which are difficult or impossible for an individual agent or monolithic system to solve. Agent systems are open and extensible systems that allow for the deployment of autonomous and proactive software components. Multi-agent systems have been brought up and used in several application domains
Logic-based Technologies for Intelligent Systems: State of the Art and Perspectives
Together with the disruptive development of modern sub-symbolic approaches to artificial intelligence (AI), symbolic approaches to classical AI are re-gaining momentum, as more and more researchers exploit their potential to make AI more comprehensible, explainable, and therefore trustworthy. Since logic-based approaches lay at the core of symbolic AI, summarizing their state of the art is of paramount importance now more than ever, in order to identify trends, benefits, key features, gaps, and limitations of the techniques proposed so far, as well as to identify promising research perspectives. Along this line, this paper provides an overview of logic-based approaches and technologies by sketching their evolution and pointing out their main application areas. Future perspectives for exploitation of logic-based technologies are discussed as well, in order to identify those research fields that deserve more attention, considering the areas that already exploit logic-based approaches as well as those that are more likely to adopt logic-based approaches in the future
Mobile Robots Navigation
Mobile robots navigation includes different interrelated activities: (i) perception, as obtaining and interpreting sensory information; (ii) exploration, as the strategy that guides the robot to select the next direction to go; (iii) mapping, involving the construction of a spatial representation by using the sensory information perceived; (iv) localization, as the strategy to estimate the robot position within the spatial map; (v) path planning, as the strategy to find a path towards a goal location being optimal or not; and (vi) path execution, where motor actions are determined and adapted to environmental changes. The book addresses those activities by integrating results from the research work of several authors all over the world. Research cases are documented in 32 chapters organized within 7 categories next described
Safe navigation and motion coordination control strategies for unmanned aerial vehicles
Unmanned aerial vehicles (UAVs) have become very popular for many military and civilian applications including in agriculture, construction, mining, environmental monitoring, etc. A desirable feature for UAVs is the ability to navigate and perform tasks autonomously with least human interaction. This is a very challenging problem due to several factors such as the high complexity of UAV applications, operation in harsh environments, limited payload and onboard computing power and highly nonlinear dynamics. Therefore, more research is still needed towards developing advanced reliable control strategies for UAVs to enable safe navigation in unknown and dynamic environments. This problem is even more challenging for multi-UAV systems where it is more efficient to utilize information shared among the networked vehicles. Therefore, the work presented in this thesis contributes towards the state-of-the-art in UAV control for safe autonomous navigation and motion coordination of multi-UAV systems. The first part of this thesis deals with single-UAV systems. Initially, a hybrid navigation framework is developed for autonomous mobile robots using a general 2D nonholonomic unicycle model that can be applied to different types of UAVs, ground vehicles and underwater vehicles considering only lateral motion. Then, the more complex problem of three-dimensional (3D) collision-free navigation in unknown/dynamic environments is addressed. To that end, advanced 3D reactive control strategies are developed adopting the sense-and-avoid paradigm to produce quick reactions around obstacles. A special case of navigation in 3D unknown confined environments (i.e. tunnel-like) is also addressed. General 3D kinematic models are considered in the design which makes these methods applicable to different UAV types in addition to underwater vehicles. Moreover, different implementation methods for these strategies with quadrotor-type UAVs are also investigated considering UAV dynamics in the control design. Practical experiments and simulations were carried out to analyze the performance of the developed methods. The second part of this thesis addresses safe navigation for multi-UAV systems. Distributed motion coordination methods of multi-UAV systems for flocking and 3D area coverage are developed. These methods offer good computational cost for large-scale systems. Simulations were performed to verify the performance of these methods considering systems with different sizes
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
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