Towards adaptive multi-robot systems: self-organization and self-adaptation

Dieser Beitrag ist mit Zustimmung des Rechteinhabers aufgrund einer (DFG geförderten) Allianz- bzw. Nationallizenz frei zugänglich.This publication is with permission of the rights owner freely accessible due to an Alliance licence and a national licence (funded by the DFG, German Research Foundation) respectively.The development of complex systems ensembles that operate in uncertain environments is a major challenge. The reason for this is that system designers are not able to fully specify the system during specification and development and before it is being deployed. Natural swarm systems enjoy similar characteristics, yet, being self-adaptive and being able to self-organize, these systems show beneficial emergent behaviour. Similar concepts can be extremely helpful for artificial systems, especially when it comes to multi-robot scenarios, which require such solution in order to be applicable to highly uncertain real world application. In this article, we present a comprehensive overview over state-of-the-art solutions in emergent systems, self-organization, self-adaptation, and robotics. We discuss these approaches in the light of a framework for multi-robot systems and identify similarities, differences missing links and open gaps that have to be addressed in order to make this framework possible

Toward a robot swarm protecting a group of migrants

Different geopolitical conflicts of recent years have led to mass migration of several civilian populations. These migrations take place in militarized zones, indicating real danger contexts for the populations. Indeed, civilians are increasingly targeted during military assaults. Defense and security needs have increased; therefore, there is a need to prioritize the protection of migrants. Very few or no arrangements are available to manage the scale of displacement and the protection of civilians during migration. In order to increase their security during mass migration in an inhospitable territory, this article proposes an assistive system using a team of mobile robots, labeled a rover swarm that is able to provide safety area around the migrants. We suggest a coordination algorithm including CNN and fuzzy logic that allows the swarm to synchronize their movements and provide better sensor coverage of the environment. Implementation is carried out using on a reduced scale rover to enable evaluation of the functionalities of the suggested software architecture and algorithms. Results bring new perspectives to helping and protecting migrants with a swarm that evolves in a complex and dynamic environment

Implementation of Robot Operating System in Beaglebone Black based Mobile Robot for Obstacle Avoidance Application

The Robot Operating System (ROS) is a collection of tools, libraries, and conventions that focus on simplifying the task of creating a complex and advanced robotics system. Its standard framework can be shared with another robotics system that has a similar platform and suitable for being introduced as an educational tool in robotics. However, the problems found out in the current robot platform available in the market are expensive and encapsulated. The development of an open source robot platform is encouraged. Therefore, this research is carried out to design and develop an ROS based obstacle avoidance system for existing differential-wheeled mobile robot. The ROS was installed under Ubuntu 14.04 on a Beaglebone Black embedded computer system. Then, the ROS was implemented together with the obstacle avoidance system to establish the communication between program nodes. The mobile robot was then designed and developed to examine the obstacle avoidance application. The debugging process was carried out to check the obstacle avoidance system application based on the communication between nodes. This process is important in examining the message publishing and subscribing from all nodes. The obstacle avoidance mobile robot has been successfully tested where the communication between nodes was running without any problem

PERFORMANCE EVALUATION AND REVIEW FRAMEWORK OF ROBOTIC MISSIONS (PERFORM): AUTONOMOUS PATH PLANNING AND AUTONOMY PERFORMANCE EVALUATION

The scope of this work spans two main areas of autonomy research 1) autonomous path planning and 2) test and evaluation of autonomous systems. Path planning is an integral part of autonomous decision-making, and a deep understanding in this area provides valuable perspective on approaching the problem of how to effectively evaluate vehicle behavior. Autonomous decision-making capabilities must include reliability, robustness, and trustworthiness in a real-world environment. A major component of robot decision-making lies in intelligent path-planning. Serving as the brains of an autonomous system, an efficient and reliable path planner is crucial to mission success and overall safety. A hybrid global and local planner is implemented using a combination of the Potential Field Method (PFM) and A-star (A*) algorithms. Created using a layered vector field strategy, this allows for flexibility along with the ability to add and remove layers to take into account other parameters such as currents, wind, dynamics, and the International Regulations for Preventing Collisions at Sea (COLGREGS). Different weights can be attributed to each layer based on the determined level of importance in a hierarchical manner. Different obstacle scenarios are shown in simulation, and proof-of-concept validation of the path-planning algorithms on an actual ASV is accomplished in an indoor environment. Results show that the combination of PFM and A* complement each other to generate a successfully planned path to goal that alleviates local minima and entrapment issues. Additionally, the planner demonstrates the ability to update for new obstacles in real time using an obstacle detection sensor. Regarding test and evaluation of autonomous vehicles, trust and confidence in autonomous behavior is required to send autonomous vehicles into operational missions. The author introduces the Performance Evaluation and Review Framework Of Robotic Missions (PERFORM), a framework for which to enable a rigorous and replicable autonomy test environment, thereby filling the void between that of merely simulating autonomy and that of completing true field missions. A generic architecture for defining the missions under test is proposed and a unique Interval Type-2 Fuzzy Logic approach is used as the foundation for the mathematically rigorous autonomy evaluation framework. The test environment is designed to aid in (1) new technology development (i.e. providing direct comparisons and quantitative evaluations of varying autonomy algorithms), (2) the validation of the performance of specific autonomous platforms, and (3) the selection of the appropriate robotic platform(s) for a given mission type (e.g. for surveying, surveillance, search and rescue). Several case studies are presented to apply the metric to various test scenarios. Results demonstrate the flexibility of the technique with the ability to tailor tests to the user’s design requirements accounting for different priorities related to acceptable risks and goals of a given mission

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

Docking solutions for smart autonomous mobile units

Dissertação de mestrado integrado em Engenharia Eletrónica Industrial e ComputadoresDocking solutions are key in the development of smart autonomous vehicles for industrial applications. Throughout the course of every autonomous vehicle workflow inside a factory, there will be moments where parking or picking cargo is needed. As these maneuvers require a precise positioning, without a correct approach, the maneuvers become ineffective jeopardizing all the automation of the process and as result, the maneuver success. Collaborating with the team of the sub-project P24 ”Autonomous Milk-Runs” result of a partnership between University of Minho and Bosch Car Multimedia Portugal S.A., this dissertation aims to conceive and develop docking maneuvers solutions for one of the prototype smart autonomous units, the stacker vehicles. In Bosch’s Braga Plant (BrgP) factory stacker vehicles are required to deliver packagings material and move finished goods within different areas on the warehouse. Stackers will then need to pick the products placed on pallets at the production lines end as the established workflow requires. This area consists in a long and narrow corridor where the stacker vehicles will need to maneuver correctly in order to pick the targeted pallets signalized by logistics. To develop a docking solution, the study of mobile vehicles kinematics, the development of behavioral based dynamics and the implementation of a pallet detection algorithm was needed to match the factory workflow and requirements. The proposed solution allows the stacker vehicles to respect their workspace constraints, with docking capabilities under multiple circumstances.Soluções de acostagem são importantes no desenvolvimento de veículos autónomos para aplicações industriais. Durante o curso das tarefas de um veículo autónomo dentro de uma fábrica, irão existir momentos em que parqueamento e o levantamento de cargas é necessário. Como estas manobras requerem um posicionamento preciso, se a abordagem não for a mais correta, as mesmas tornam-se obsoletas, colocando em causa toda a automatização do processo e, como consequência, o seu sucesso. Colaborando com a equipa do sub-projeto P24 ”Autonomous Milk-Runs” resultante da parceria entre a Universidade do Minho e a Bosch Car Multimedia Portugal S.A., esta dissertação aponta à conceção e desenvolvimento de soluções para manobras de acoplamento para uma das unidades autónomas inteligentes em análise, os empilhadores. Na fábrica da Bosch Braga Plant (BrgP), é requerido aos veículos empilhadores a entrega de bens finalizados dentro de diferentes áreas no armazém. Os empilhadores deverão então levantar os produtos colocados em paletes no final da linhas de produção, tal como o fluxo de trabalho estabelecido para estes indica. Esta área consiste em um longo e apertado corredor, onde os veículos empilhadores irão necessitar de manobrar corretamente de modo a levantar as paletes alvo sinalizadas pela logística. Para a desenvolver uma solução de acoplamento, o estudo da cinemática de veículos móveis, o desenvolvimento de uma dinâmica baseada em comportamento e a implementação de um algoritmo de deteção de paletes foram necessários de modo a cumprir com os requisitos e fluxo de trabalho impostos pela empresa. A solução proposta permite aos veículos empilhadores respeitarem o seu espaço de trabalho, tendo capacidade de acoplamento para circunstâncias múltiplas

Flexible Composition of Robot Logic with Computer Vision Services

Vision-based robotics is an ever-growing field within industrial automation. Demands for greater flexibility and higher quality motivate manufacturing companies to adopt these technologies for such tasks as material handling, assembly, and inspection. In addition to the direct use in the manufacturing setting, robots combined with vision systems serve as highly flexible means for realization of prototyping test-beds in the R&D context.Traditionally, the problem areas of robotics and computer vision are attacked separately. An exception is the study of vision-based servo control, the focus of which constitutes control-theoretic aspects of vision-based robot guidance under assumption that robot joints can be controlled directly. The missing part is a systemic approach to implementing robotic application with vision sensing given industrial robots constrained by their programming interface. This thesis targets the development process of vision-based robotic systems in an event-driven environment. It focuses on design and composition of three functional components: (1) robot control function, (2) image acquisition function, and (3) image processing function. The thesis approaches its goal by a combination of laboratory results, a case study of an industrial company (Kongsberg Automotive AS), and formalization of computational abstractions and architectural solutions. The image processing function is tackled with the application of reactive pipelines. The proposed system development method allows for smooth transition from early-stage vision algorithm prototyping to the integration phase. The image acquisition function in this thesis is exposed in a service-oriented manner with the help of a flexible set of concurrent computational primitives. To realize control of industrial robots, a distributed architecture is devised, which supports composability of communication-heavy robot logic, as well as flexible coupling of the robot control node with vision services