Collision Free Navigation of a Multi-Robot Team for Intruder Interception

In this report, we propose a decentralised motion control algorithm for the mobile robots to intercept an intruder entering (k-intercepting) or escaping (e-intercepting) a protected region. In continuation, we propose a decentralized navigation strategy (dynamic-intercepting) for a multi-robot team known as predators to intercept the intruders or in the other words, preys, from escaping a siege ring which is created by the predators. A necessary and sufficient condition for the existence of a solution of this problem is obtained. Furthermore, we propose an intelligent game-based decision-making algorithm (IGD) for a fleet of mobile robots to maximize the probability of detection in a bounded region. We prove that the proposed decentralised cooperative and non-cooperative game-based decision-making algorithm enables each robot to make the best decision to choose the shortest path with minimum local information. Then we propose a leader-follower based collision-free navigation control method for a fleet of mobile robots to traverse an unknown cluttered environment where is occupied by multiple obstacles to trap a target. We prove that each individual team member is able to traverse safely in the region, which is cluttered by many obstacles with any shapes to trap the target while using the sensors in some indefinite switching points and not continuously, which leads to saving energy consumption and increasing the battery life of the robots consequently. And finally, we propose a novel navigation strategy for a unicycle mobile robot in a cluttered area with moving obstacles based on virtual field force algorithm. The mathematical proof of the navigation laws and the computer simulations are provided to confirm the validity, robustness, and reliability of the proposed methods

Marine Robots for Underwater Surveillance

Abstract Purpose of Review The paper reviews the role of marine robots, in particular unmanned vehicles, in underwater surveillance, i.e. the control and monitoring of an area of competence aimed at identifying potential threats in support of homeland defence, antiterrorism, force protection and Explosive Ordnance Disposal (EOD). Recent Findings The paper explores separately robotic missions for identification and classification of threats lying on the seabed (e.g. EOD) and anti-intrusion robotic systems. The current main scientific challenge is identified in terms of enhancing autonomy and team/swarm mission capabilities by improving interoperability among robotic vehicles and providing communication networking capabilities, a non-trivial task, giving the severe limitations in bandwidth and latency of acoustic underwater messaging. Summary The work is intended to be a critical guide to the recent prolific bibliography on the topic, providing pointers to the main recent advancements in the field, and to give also a set of references in terms of mission and stakeholders' requirements (port authorities, coastal guards, navies)

Advanced Air and Missile Defense under Spatial Grasp Technology

A novel control ideology and technology for solving tasks in large distributed networked systems will be briefed. Based on active scenarios self-navigating and self-matching distributed spaces in a highly organized super-virus mode, it can effectively establish global control over large systems of any natures. The technology can use numerous scattered and dissimilar facilities in an integral and holistic way, allow-ing them to work together in goal-driven supercomputer mode. The approach can be useful for advanced air and missile defense in a variety of ways, some of which described and explained in this paper. The re-lated material has been accepted for presentation at The 12th 3AF Integrated Air and Missile Defence in-ternational conference, June 27–29, Stockholm, Sweden, http://3af-integratedairmissiledefence.com.Коротко викладено нову ідеологію та технологію керування для вирішення задач у великих мережевих системах. Запропонований підхід, який базується на активних сценаріях, що здійснюють самонавігацію і самосинхронізацію в розподілених просторах у режимі організованого супервіруса, може встановлювати глобальний контроль над системами довільної природи. Технологія дозволяє ефективно інтегрувати безліч розрізнених та неоднорідних об’єктів, дозволяючи їм працювати разом у цілеспрямованому суперкомп’ютерному режимі. Вона може бути корисною для перспективної протиповітряної та протиракетної оборони різними способами; деякі з них викладені та пояснені у цій статті. Відповідний матеріал прийнятий для презентації на 12-й Міжнародній конференції з Інтегрованої протиповітряної і протиракетної оборони, 27–29 червня в Стокгольмі, Швеція, http://3af-integratedairmissiledefence.com.Кратко изложены новая идеология и технология управления для решения задач в больших сетевых системах. Предложенный подход, основанный на активных сценариях, осуществляющих самонавигацию и самосинхронизацию в распределенных пространствах в режиме организованного супервируса, может устанавливать глобальный контроль над системами любой природы. Технология позволяет эффективно интегрировать множество разрозненных и разнородных объектов, позволяя им работать совместно в целенаправленном суперкомпьютерном режиме. Она может быть полезна для перспективной противовоздушной и противоракетной обороны разными способами; некоторые из них изложены и объяснены в этой статье. Соответствующий материал принят для представления на 12-й Международной конференции по интегрированной противовоздушной и противоракетной обороне, 27–29 июня в Стокгольме, Швеция, http://3af-integratedairmissiledefence.com

Multi-sensor data fusion techniques for RPAS detect, track and avoid

Accurate and robust tracking of objects is of growing interest amongst the computer vision scientific community. The ability of a multi-sensor system to detect and track objects, and accurately predict their future trajectory is critical in the context of mission- and safety-critical applications. Remotely Piloted Aircraft System (RPAS) are currently not equipped to routinely access all classes of airspace since certified Detect-and-Avoid (DAA) systems are yet to be developed. Such capabilities can be achieved by incorporating both cooperative and non-cooperative DAA functions, as well as providing enhanced communications, navigation and surveillance (CNS) services. DAA is highly dependent on the performance of CNS systems for Detection, Tacking and avoiding (DTA) tasks and maneuvers. In order to perform an effective detection of objects, a number of high performance, reliable and accurate avionics sensors and systems are adopted including non-cooperative sensors (visual and thermal cameras, Laser radar (LIDAR) and acoustic sensors) and cooperative systems (Automatic Dependent Surveillance-Broadcast (ADS-B) and Traffic Collision Avoidance System (TCAS)). In this paper the sensors and system information candidates are fully exploited in a Multi-Sensor Data Fusion (MSDF) architecture. An Unscented Kalman Filter (UKF) and a more advanced Particle Filter (PF) are adopted to estimate the state vector of the objects based for maneuvering and non-maneuvering DTA tasks. Furthermore, an artificial neural network is conceptualised/adopted to exploit the use of statistical learning methods, which acts to combined information obtained from the UKF and PF. After describing the MSDF architecture, the key mathematical models for data fusion are presented. Conceptual studies are carried out on visual and thermal image fusion architectures

Assistive multimodal robotic system (AMRSys): security and privacy issues, challenges, and possible solutions

Assistive robotic systems could be a suitable solution to support a variety of health and care services, help independent living, and even simulate affection, to reduce loneliness. However, adoption is limited by several issues, as well as user concerns about ethics, data security, and privacy. Other than the common threats related to internet connectivity, personal robotic systems have advanced interaction possibilities, such as audio, video, touch, and gestures, which could be exploited to gain access to private data that are stored in the robot. Therefore, novel, safer methods of interaction should be designed to safeguard users’ privacy. To solicit further research on secure and private multimodal interaction, this article presents a thorough study of the state-of-the-art literature on data security and user privacy in interactive social robotic systems for health and care. In our study, we focus on social robotics to assist older people, which is a global challenge that is receiving a great deal of attention from the robotics and social care communities. This application will have a significant positive impact on the economy and society, but poses various security and privacy issues. This article analyses the key vulnerable areas where data leakage could occur during a multimodal interaction with a personal assistive robotic system. Thus, blockchain with a resource-aware framework, along with a continuous multifactor authentication mechanism, are envisaged as a potential solution for making such systems secure by design; therefore, increasing trust, acceptability, and adoption. Among the key cybersecurity research challenges, it is crucial to create an intelligent mechanism that autonomously determines the right trade-off between continuous user prompts and system usability, according to data types and personal preferences