An idiotypic immune network as a short-term learning architecture for mobile robots

A combined Short-Term Learning (STL) and Long-Term Learning (LTL) approach to solving mobile robot navigation problems is presented and tested in both real and simulated environments. The LTL consists of rapid simulations that use a Genetic Algorithm to derive diverse sets of behaviours. These sets are then transferred to an idiotypic Artificial Immune System (AIS), which forms the STL phase, and the system is said to be seeded. The combined LTL-STL approach is compared with using STL only, and with using a handdesigned controller. In addition, the STL phase is tested when the idiotypic mechanism is turned off. The results provide substantial evidence that the best option is the seeded idiotypic system, i.e. the architecture that merges LTL with an idiotypic AIS for the STL. They also show that structurally different environments can be used for the two phases without compromising transferability.

A ROS-based software architecture for a versatile collaborative dual-armed autonomous mobile robot for the manufacturing industry

The industrial context is changing rapidly due to advancements in technology fueled by the Internet and Information Technology. The fourth industrial revolution counts integration, flexibility, and optimization as its fundamental pillars, and, in this context, Human-Robot Collaboration has become a crucial factor for manufacturing sustainability in Europe. Collaborative robots are appealing to many companies due to their low installation and running costs and high degree of flexibility, making them ideal for reshoring production facilities with a short return on investment. The ROSSINI European project aims to implement a true Human-Robot Collaboration by designing, developing, and demonstrating a modular and scalable platform for integrating human-centred robotic technologies in industrial production environments. The project focuses on safety concerns related to introducing a cobot in a shared working area and aims to lay the groundwork for a new working paradigm at the industrial level. The need for a software architecture suitable to the robotic platform employed in one of three use cases selected to deploy and test the new technology was the main trigger of this Thesis. The chosen application consists of the automatic loading and unloading of raw-material reels to an automatic packaging machine through an Autonomous Mobile Robot composed of an Autonomous Guided Vehicle, two collaborative manipulators, and an eye-on-hand vision system for performing tasks in a partially unstructured environment. The results obtained during the ROSSINI use case development were later used in the SENECA project, which addresses the need for robot-driven automatic cleaning of pharmaceutical bins in a very specific industrial context. The inherent versatility of mobile collaborative robots is evident from their deployment in the two projects with few hardware and software adjustments. The positive impact of Human-Robot Collaboration on diverse production lines is a motivation for future investments in research on this increasingly popular field by the industry.

Factors affecting the mission time of an autonomous mobile robot: a theoretical and experimental investigation

I vantaggi dell’Industria 4.0 hanno stravolto il manufacturing. Ma cosa vuol dire "Industria 4.0"? Essa è la nuova frontiera del manufacturing, basata su princìpi che seguono i passi avanti dei sistemi IT e della tecnologia. Dunque, i suoi pilastri sono: integrazione, verticale e orizzontale, digitalizzazione e automazione. L’Industria 4.0 coinvolge molte aree della supply chain, dai flussi informativi alla logistica. In essa e nell’intralogistica, la priorità è sviluppare dei sistemi di material handling flessibili, automatizzati e con alta prontezza di risposta. Il modello ideale è autonomo, in cui i veicoli fanno parte di una flotta le cui decisioni sono rese decentralizzate grazie all'alta connettività e alla loro abilità di collezionare dati e scambiarli rapidamente nel cloud aziendale.Tutto ciò non sarebbe raggiungibile se ci si affidasse a un comune sistema di trasporto AGV, troppo rigido e centralizzato. La tesi si focalizza su un tipo di material handlers più flessibile e intelligente: gli Autonomous Mobile Robots. Grazie alla loro intelligenza artificiale e alla digitalizzazione degli scambi di informazioni, interagiscono con l’ambiente per evitare ostacoli e calcolare il percorso ottimale. Gli scenari dell’ambiente lavorativo determinano perdite di tempo nel tragitto dei robot e sono queste che dovremo studiare. Nella tesi, i vantaggi apportati dagli AMR, come la loro decentralizzazione delle decisioni, saranno introdotti mediante una literature review e poi l’attenzione verterà sull’analisi di ogni scenario di lavoro. Fondamentali sono state le esperienze nel Logistics 4.0 Lab di NTNU, per ricreare fisicamente alcuni scenari. Inoltre, il software AnyLogic sarà usato per riprodurre e simulare tutti gli scenari rilevanti. I risultati delle simulazioni verranno infine usati per creare un modello che associ ad ogni scenario rilevante una perdita di tempo, attraverso una funzione. Per questo saranno usati software di data analysis come Minitab e MatLab.

Object recognition for autonomous objects: comparison of two approaches

Report for the scientific sojourn at the Swiss Federal Institute of Technology Zurich, Switzerland, between September and December 2007. In order to make robots useful assistants for our everyday life, the ability to learn and recognize objects is of essential importance. However, object recognition in real scenes is one of the most challenging problems in computer vision, as it is necessary to deal with difficulties. Furthermore, in mobile robotics a new challenge is added to the list: computational complexity. In a dynamic world, information about the objects in the scene can become obsolete before it is ready to be used if the detection algorithm is not fast enough. Two recent object recognition techniques have achieved notable results: the constellation approach proposed by Lowe and the bag of words approach proposed by Nistér and Stewénius. The Lowe constellation approach is the one currently being used in the robot localization project of the COGNIRON project. This report is divided in two main sections. The first section is devoted to briefly review the currently used object recognition system, the Lowe approach, and bring to light the drawbacks found for object recognition in the context of indoor mobile robot navigation. Additionally the proposed improvements for the algorithm are described. In the second section the alternative bag of words method is reviewed, as well as several experiments conducted to evaluate its performance with our own object databases. Furthermore, some modifications to the original algorithm to make it suitable for object detection in unsegmented images are proposed.

Localização de um robô móvel usando odometria e marcos naturais

Several methods of mobile robot navigation request the mensuration of robot position and orientation in its workspace. In the wheeled mobile robot case, techniques based on odometry allow to determine the robot localization by the integration of incremental displacements of its wheels. However, this technique is subject to errors that accumulate with the distance traveled by the robot, making unfeasible its exclusive use. Other methods are based on the detection of natural or artificial landmarks present in the environment and whose location is known. This technique doesnt generate cumulative errors, but it can request a larger processing time than the methods based on odometry. Thus, many methods make use of both techniques, in such a way that the odometry errors are periodically corrected through mensurations obtained from landmarks. Accordding to this approach, this work proposes a hybrid localization system for wheeled mobile robots in indoor environments based on odometry and natural landmarks. The landmarks are straight lines de.ned by the junctions in environments floor, forming a bi-dimensional grid. The landmark detection from digital images is perfomed through the Hough transform. Heuristics are associated with that transform to allow its application in real time. To reduce the search time of landmarks, we propose to map odometry errors in an area of the captured image that possesses high probability of containing the sought mark

Sistema de navegação para robôs móveis autônomos

The main task and one of the major mobile robotics problems is its navigation process. Conceptualy, this process means drive the robot from an initial position and orientation to a goal position and orientation, along an admissible path respecting the temporal and velocity constraints. This task must be accomplished by some subtasks like robot localization in the workspace, admissible path planning, trajectory generation and motion control. Moreover, autonomous wheeled mobile robots have kinematics constraints, also called nonholonomic constraints, that impose the robot can not move everywhere freely in its workspace, reducing the number of feasible paths between two distinct positions. This work mainly approaches the path planning and trajectory generation problems applied to wheeled mobile robots acting on a robot soccer environment. The major dificulty in this process is to find a smooth function that respects the imposed robot kinematic constraints. This work proposes a path generation strategy based on parametric polynomials of third degree for the 'x' and 'y' axis. The 'theta' orientation is derived from the 'y' and 'x' relations in such a way that the generated path respects the kinematic constraint. To execute the trajectory, this work also shows a simple control strategy acting on the robot linear and angular velocities

Desenvolvimento de um sistema de navegação baseado em máquina de vetores de suporte para dirigibilidade de um robô móvel por caminhos em plantações

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Desenvolvimento de um sistema para navegação de robôs móveis por caminhos em plantações

The use of mobile robots in the agriculture turns out to be interesting in tasks of cultivation and application of pesticides in minute quantities to reduce environmental pollution. In this paper we present the development of a system to control an autonomous mobile robot navigation through tracks in plantations. Track images are used to control robot direction by preprocessing them to extract image features, and then submitting such characteristic features to a support vector machine to find out the most appropriate route. As the overall goal of the project to which this work is connected is the robot control in real time, the system will be embedded onto a hardware platform. However, in this paper we report the software implementation of a support vector machine, which so far presented around 93% accuracy in predicting the appropriate route.

Navegação de um robô móvel baseado em um modelo de consciência artificial

This work presents a study about a the Baars-Franklin architecture, which defines a model of computational consciousness, and use it in a mobile robot navigation task. The insertion of mobile robots in dynamic environments carries a high complexity in navigation tasks, in order to deal with the constant environment changes, it is essential that the robot can adapt to this dynamism. The approach utilized in this work is to make the execution of these tasks closer to how human beings react to the same conditions by means of a model of computational consci-ousness. The LIDA architecture (Learning Intelligent Distribution Agent) is a cognitive system that seeks tomodel some of the human cognitive aspects, from low-level perceptions to decision making, as well as attention mechanism and episodic memory. In the present work, a computa-tional implementation of the LIDA architecture was evaluated by means of a case study, aiming to evaluate the capabilities of a cognitive approach to navigation of a mobile robot in dynamic and unknown environments, using experiments both with virtual environments (simulation) and a real robot in a realistic environment. This study concluded that it is possible to obtain benefits by using conscious cognitive models in mobile robot navigation tasks, presenting the positive and negative aspects of this approach.

Integration of a mobile autonomous robot in a surveillance multi-agent system

This dissertation aims to guarantee the integration of a mobile autonomous robot equipped with many sensors in a multi-agent distributed and georeferenced surveillance system. The integration of a mobile autonomous robot in this system leads to new features that will be available to clients of surveillance system may use. These features may be of two types: using the robot as an agent that will act in the environment or by using the robot as a mobile set of sensors. As an agent in the system, the robot can move to certain locations when alerts are received, in order to acknowledge the underlying events or take to action in order to assist in resolving this event. As a sensor platform in the system, it is possible to access information that is read from the sensors of the robot and access complementary measurements to the ones taken by other sensors in the multi-agent system. To integrate this mobile robot in an effective way it is necessary to extend the current multi-agent system architecture to make the connection between the two systems and to integrate the functionalities provided by the robot into the multi-agent system.

Generating timed trajectories foran autonomous robot

Tese de Doutoramento Programa Doutoral em Engenharia Electrónica e Computadores

WMR navigation using local potential field corridors and narrow local occupancy grid perception

Path planning and control strategies applied to autonomous mobile robots should fulfil safety rules as well as achieve final goals. Trajectory planning applications should be fast and flexible to allow real time implementations as well as environment interactions. The methodology presented uses the on robot information as the meaningful data necessary to plan a narrow passage by using a corridor based on attraction potential fields that approaches the mobile robot to the final desired configuration. It employs local and dense occupancy grid perception to avoid collisions. The key goals of this research project are computational simplicity as well as the possibility of integrating this method with other methods reported by the research community. Another important aspect of this work consist in testing the proposed method by using a mobile robot with a perception system composed of a monocular camera and odometers placed on the two wheels of the differential driven motion system. Hence, visual data are used as a local horizon of perception in which trajectories without collisions are computed by satisfying final goal approaches and safety criteria

An overview of the advantages and constraints of coded pattern projection techniques for autonomous navigation

The absolute necessity of obtaining 3D information of structured and unknown environments in autonomous navigation reduce considerably the set of sensors that can be used. The necessity to know, at each time, the position of the mobile robot with respect to the scene is indispensable. Furthermore, this information must be obtained in the least computing time. Stereo vision is an attractive and widely used method, but, it is rather limited to make fast 3D surface maps, due to the correspondence problem. The spatial and temporal correspondence among images can be alleviated using a method based on structured light. This relationship can be directly found codifying the projected light; then each imaged region of the projected pattern carries the needed information to solve the correspondence problem. We present the most significant techniques, used in recent years, concerning the coded structured light method

Quadcopter assistant for a mobile assembly robot

Science has revolutionized the human life. The advance progress in science and research is making human life easier and more comfortable. The new and emerging technology of micro drone is penetrating and widening the scientific research. This thesis is a part of work in which a unique work is carried out, although related research paper and journal are available. Design and development of automatic charging station for a ready to fly quadcopter is rare and unusual work. The work is carried out as an standard engineering process that include requirements gathering, creating the required document (this thesis is a part of required document as well), selection of suitable hardware, configuring the hardware, generate the code for software, uploading code to the microcontroller, troubleshooting and rectification, finalized prototype and testing. Thesis describe how mechatronics engineering is useful in generating a customized and unique project. At the starting phase of this project (before purchasing a ready to fly quadcopter) every single aspect of this work was known. The only unknown alternatives was a battery and charger. Several task was achieved including design and development of automatic charging station, accurate landing and telecast a live video on additional screen. At starting it was decided that quadcopter should follow the mobile robot, during study it was concluded there is no such quadcopter available in market to auto follow a robot indoor. This works starts with a market survey and comparing the different brands of quadcopter that meets all the requirements and specifications of the mobile robot assembly. Selection of quadcopter is a result of discussion and meeting with the team members, supervisor, professor and project manage.

Design and implementation of machine vision system for the mobile assembly robot

The review of intelligent machines shows that the demand for new ways of helping people in perception of the real world is becoming higher and higher every year. This thesis provides information about design and implementation of machine vision for mobile assembly robot. The work has been done as a part of LUT project in Laboratory of Intelligent Machines. The aim of this work is to create a working vision system. The qualitative and quantitative research were done to complete this task. In the first part, the author presents the theoretical background of such things as digital camera work principles, wireless transmission basics, creation of live stream, methods used for pattern recognition. Formulas, dependencies and previous research related to the topic are shown. In the second part, the equipment used for the project is described. There is information about the brands, models, capabilities and also requirements needed for implementation. Although, the author gives a description of LabVIEW software, its add-ons and OpenCV which are used in the project. Furthermore, one can find results in further section of considered thesis. They mainly represented by screenshots from cameras, working station and photos of the system. The key result of this thesis is vision system created for the needs of mobile assembly robot. Therefore, it is possible to see graphically what was done on examples. Future research in this field includes optimization of the pattern recognition algorithm. This will give less response time for recognizing objects. Presented by author system can be used also for further activities which include artificial intelligence usage.