3D multi-robot patrolling with a two-level coordination strategy

Teams of UGVs patrolling harsh and complex 3D environments can experience interference and spatial conflicts with one another. Neglecting the occurrence of these events crucially hinders both soundness and reliability of a patrolling process. This work presents a distributed multi-robot patrolling technique, which uses a two-level coordination strategy to minimize and explicitly manage the occurrence of conflicts and interference. The first level guides the agents to single out exclusive target nodes on a topological map. This target selection relies on a shared idleness representation and a coordination mechanism preventing topological conflicts. The second level hosts coordination strategies based on a metric representation of space and is supported by a 3D SLAM system. Here, each robot path planner negotiates spatial conflicts by applying a multi-robot traversability function. Continuous interactions between these two levels ensure coordination and conflicts resolution. Both simulations and real-world experiments are presented to validate the performances of the proposed patrolling strategy in 3D environments. Results show this is a promising solution for managing spatial conflicts and preventing deadlocks

A COLLISION AVOIDANCE SYSTEM FOR AUTONOMOUS UNDERWATER VEHICLES

The work in this thesis is concerned with the development of a novel and practical collision avoidance system for autonomous underwater vehicles (AUVs). Synergistically, advanced stochastic motion planning methods, dynamics quantisation approaches, multivariable tracking controller designs, sonar data processing and workspace representation, are combined to enhance significantly the survivability of modern AUVs. The recent proliferation of autonomous AUV deployments for various missions such as seafloor surveying, scientific data gathering and mine hunting has demanded a substantial increase in vehicle autonomy. One matching requirement of such missions is to allow all the AUV to navigate safely in a dynamic and unstructured environment. Therefore, it is vital that a robust and effective collision avoidance system should be forthcoming in order to preserve the structural integrity of the vehicle whilst simultaneously increasing its autonomy. This thesis not only provides a holistic framework but also an arsenal of computational techniques in the design of a collision avoidance system for AUVs. The design of an obstacle avoidance system is first addressed. The core paradigm is the application of the Rapidly-exploring Random Tree (RRT) algorithm and the newly developed version for use as a motion planning tool. Later, this technique is merged with the Manoeuvre Automaton (MA) representation to address the inherent disadvantages of the RRT. A novel multi-node version which can also address time varying final state is suggested. Clearly, the reference trajectory generated by the aforementioned embedded planner must be tracked. Hence, the feasibility of employing the linear quadratic regulator (LQG) and the nonlinear kinematic based state-dependent Ricatti equation (SDRE) controller as trajectory trackers are explored. The obstacle detection module, which comprises of sonar processing and workspace representation submodules, is developed and tested on actual sonar data acquired in a sea-trial via a prototype forward looking sonar (AT500). The sonar processing techniques applied are fundamentally derived from the image processing perspective. Likewise, a novel occupancy grid using nonlinear function is proposed for the workspace representation of the AUV. Results are presented that demonstrate the ability of an AUV to navigate a complex environment. To the author's knowledge, it is the first time the above newly developed methodologies have been applied to an A UV collision avoidance system, and, therefore, it is considered that the work constitutes a contribution of knowledge in this area of work.J&S MARINE LT

Ein mobiler Serviceroboter zur Automatisierung der Probenahme und des Probenmanagements in einem biotechnologischen Pilotlabor

Scherer T. A mobile service robot for automisation of sample taking and sample management in a biotechnological pilot laboratory. Bielefeld (Germany): Bielefeld University; 2004.In biotechnologischen Laboratorien ist die Qualität der typischerweise pharmazeutischen Produkte ein wortwörtlich lebenswichtiges Ziel. Die Qualität der Zellkultivierungen wurde historisch nur durch off-line Messungen von physikalischen Prozessparametern wie pH und pO2 sichergestellt. Biologische Parameter wie die Zelldichte und -viabilität wurden nur off-line gemessen, weil das dazu notwendige Probenmanagement hochkomplizierte Manipulationen und Analysen beinhaltet und deshalb nicht automatisiert werden konnte. Es gibt zwar mehrere automatisierte Geräte, um einem Labortechniker zu assistieren, aber kein System, welches das gesamte Probenmanagement automatisiert. In dieser Arbeit wird ein neuer Typ von Serviceroboter präsentiert, der aus einem auf einer mobilen Plattform montierten Roboterarm besteht und diese Lücke schließt. Dieser Roboter muss eine ganze Reihe von Problemen bewältigen: Er muss seine Position im Labor bestimmen können (Lokalisation), er muss eine kollisionsfreie Bahn zu den beteiligten Geräten finden können (Bahnplanung mit Hindernisvermeidung), er darf bei seinen Bewegungen keine Menschen gefährden oder Laborausrüstung beschädigen (Kollisionsvermeidung), er muss die zu bedienenden Geräte erkennen und ihre Position präzise messen können (Bildverarbeitung), er muss sie bedienen können (Armsteuerung), er muss Objekte greifen können (Greifer und Finger) und er muss sie gefügig handhaben können, um sie nicht zu beschädigen (Kraftregelung). Er muss autonom sein, um nur die allernotwendigste Menge an Benutzereingriffen zu benötigen, und doch durch ein Laborsteuerprogramm kontrollierbar sein, um Eingriffe zu erlauben. Schließlich muss er einfach durch ungeschultes Personal zu warten sein. All diese Aspekte werden von dem in dieser Arbeit präsentierten neuen Robotersystem abgedeckt.In biotechnolgical laboratories, the quality of the typically pharmaceutical product is a literally life-important goal. Historically, the quality of the cell cultivations was ensured by on-line measurements of physical process parameters like pH and pO2 only. Biological parameters like cell density and viability were only measured off-line, because the necessary sample management involves highly complicated manipulations and analyses and could therefore not be automated. Various automated devices to assist a laboratory technician do exist, but so far no system to automate the entire sample management. In this work a novel type of service robot consisting of a robot arm mounted on a mobile platform is presented that closes this gap. This robot has to master a multitude of problems: It must be able to locate its position in the laboratory (localisation), it must be able to find a collision-free path to the involved devices (path planning with obstacle avoidance), it must not endanger humans or damage laboratory equipment while moving (collision avoidance), it must be able to recognize the devices to be manipulated and measure their precise position (computer vision), it must be able to manipulate them (arm control), it must be able to grasp objects (gripper and fingers) and it must be able to handle them with compliance in order to not damage them (force control). It must be autonomous in order to only require the least possible amount of user intervention, and yet controllable by a laboratory control program in order to allow intervention. Finally, it must be easily maintainable by non-expert personell. All these aspects are covered by the novel robot system presented in this thesis

A review of artificial intelligence applied to path planning in UAV swarms

This version of the article has been accepted for publication, after peer review and is subject to Springer Nature’s AM terms of use, but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: https://doi.org/10.1007/ s00521-021-06569-4This is the accepted version of: A. Puente-Castro, D. Rivero, A. Pazos, and E. Fernández-Blanco, "A review of artificial intelligence applied to path planning in UAV swarms", Neural Computing and Applications, vol. 34, pp. 153–170, 2022. https://doi.org/10.1007/s00521-021-06569-4[Abstract]: Path Planning problems with Unmanned Aerial Vehicles (UAVs) are among the most studied knowledge areas in the related literature. However, few of them have been applied to groups of UAVs. The use of swarms allows to speed up the flight time and, thus, reducing the operational costs. When combined with Artificial Intelligence (AI) algorithms, a single system or operator can control all aircraft while optimal paths for each one can be computed. In order to introduce the current situation of these AI-based systems, a review of the most novel and relevant articles was carried out. This review was performed in two steps: first, a summary of the found articles; second, a quantitative analysis of the publications found based on different factors, such as the temporal evolution or the number of articles found based on different criteria. Therefore, this review provides not only a summary of the most recent work but it gives an overview of the trend in the use of AI algorithms in UAV swarms for Path Planning problems. The AI techniques of the articles found can be separated into four main groups based on their technique: reinforcement Learning techniques, Evolutive Computing techniques, Swarm Intelligence techniques, and, Graph Neural Networks. The final results show an increase in publications in recent years and that there is a change in the predominance of the most widely used techniques.This work is supported by Instituto de Salud Carlos III, grant number PI17/01826 (Collaborative Project in Genomic Data Integration (CICLOGEN) funded by the Instituto de Salud Carlos III from the Spanish National plan for Scientific and Technical Research and Innovation 2013–2016 and the European Regional Development Funds (FEDER)—“A way to build Europe.”. This project was also supported by the General Directorate of Culture, Education and University Management of Xunta de Galicia ED431D 2017/16 and “Drug Discovery Galician Network” Ref. ED431G/01 and the “Galician Network for Colorectal Cancer Research” (Ref. ED431D 2017/23). This work was also funded by the grant for the consolidation and structuring of competitive research units (ED431C 2018/49) from the General Directorate of Culture, Education and University Management of Xunta de Galicia, and the CYTED network (PCI2018_093284) funded by the Spanish Ministry of Ministry of Innovation and Science. This project was also supported by the General Directorate of Culture, Education and University Management of Xunta de Galicia “PRACTICUM DIRECT” Ref. IN845D-2020/03.Xunta de Galicia; ED431D 2017/16Xunta de Galicia; ED431G/01Xunta de Galicia; ED431D 2017/23Xunta de Galicia; ED431C 2018/49Xunta de Galicia; IN845D-2020/0

Proceedings of the 9th Conference on Autonomous Robot Systems and Competitions

Welcome to ROBOTICA 2009. This is the 9th edition of the conference on Autonomous Robot Systems and Competitions, the third time with IEEE‐Robotics and Automation Society Technical Co‐Sponsorship. Previous editions were held since 2001 in Guimarães, Aveiro, Porto, Lisboa, Coimbra and Algarve. ROBOTICA 2009 is held on the 7th May, 2009, in Castelo Branco , Portugal. ROBOTICA has received 32 paper submissions, from 10 countries, in South America, Asia and Europe. To evaluate each submission, three reviews by paper were performed by the international program committee. 23 papers were published in the proceedings and presented at the conference. Of these, 14 papers were selected for oral presentation and 9 papers were selected for poster presentation. The global acceptance ratio was 72%. After the conference, eighth papers will be published in the Portuguese journal Robótica, and the best student paper will be published in IEEE Multidisciplinary Engineering Education Magazine. Three prizes will be awarded in the conference for: the best conference paper, the best student paper and the best presentation. The last two, sponsored by the IEEE Education Society ‐ Student Activities Committee. We would like to express our thanks to all participants. First of all to the authors, whose quality work is the essence of this conference. Next, to all the members of the international program committee and reviewers, who helped us with their expertise and valuable time. We would also like to deeply thank the invited speaker, Jean Paul Laumond, LAAS‐CNRS France, for their excellent contribution in the field of humanoid robots. Finally, a word of appreciation for the hard work of the secretariat and volunteers. Our deep gratitude goes to the Scientific Organisations that kindly agreed to sponsor the Conference, and made it come true. We look forward to seeing more results of R&D work on Robotics at ROBOTICA 2010, somewhere in Portugal