Energy Management Module for Mobile Robots in Hostile Environments

In hostile environments at CERN and other similar scientific facilities, having a reliable mobile robot system is essential for successful execution of robotic missions and to avoid situations of manual recovery of the robots in the event that the robot runs out of energy. Because of environmental constraints, such mobile robots are usually battery-powered and hence energy management and optimization is one of the key challenges in this field. The ability to know beforehand the energy consumed by various elements of the robot (such as locomotion, sensors, controllers, computers and communication) will allow flexibility in planning or managing the tasks to be performed by the robot.

Human-robot interaction for telemanipulation in large workspaces

Independientemente de la existencia de técnicas altamente sofisticadas y capacidades de cómputo cada vez más elevadas, los problemas asociados a los robots que interactúan con entornos no estructurados siguen siendo un desafío abierto en robótica. A pesar de los grandes avances de los sistemas robóticos autónomos, hay algunas situaciones en las que una persona en el bucle sigue siendo necesaria. Ejemplos de esto son, tareas en entornos de fusión nuclear, misiones espaciales, operaciones submarinas y cirugía robótica. Esta necesidad se debe a que las tecnologías actuales no pueden realizar de forma fiable y autónoma cualquier tipo de tarea. Esta tesis presenta métodos para la teleoperación de robots abarcando distintos niveles de abstracción que van desde el control supervisado, en el que un operador da instrucciones de alto nivel en la forma de acciones, hasta el control bilateral, donde los comandos toman la forma de señales de control de bajo nivel. En primer lugar, se presenta un enfoque para llevar a cabo la teleoperación supervisada de robots humanoides. El objetivo es controlar robots terrestres capaces de ejecutar tareas complejas en entornos de búsqueda y rescate utilizando enlaces de comunicación limitados. Esta propuesta incorpora comportamientos autónomos que el operador puede utilizar para realizar tareas de navegación y manipulación mientras se permite cubrir grandes áreas de entornos remotos diseñados para el acceso de personas. Los resultados experimentales demuestran la eficacia de los métodos propuestos. En segundo lugar, se investiga el uso de dispositivos rentables para telemanipulación guiada. Se presenta una aplicación que involucra un robot humanoide bimanual y un traje de captura de movimiento basado en sensores inerciales. En esta aplicación, se estudian las capacidades de adaptación introducidas por el factor humano y cómo estas pueden compensar la falta de sistemas robóticos de alta precisión. Este trabajo es el resultado de una colaboración entre investigadores del Biorobotics Laboratory de la Universidad de Harvard y el Centro de Automática y Robótica UPM-CSIC. En tercer lugar, se presenta un nuevo controlador háptico que combina velocidad y posición. Este controlador bilateral híbrido hace frente a los problemas relacionados con la teleoperación de un robot esclavo con un gran espacio de trabajo usando un dispositivo háptico pequeño como maestro. Se pueden cubrir amplias áreas de trabajo al cambiar automáticamente entre los modos de control de velocidad y posición. Este controlador háptico es ideal para sistemas maestro-esclavo con cinemáticas diferentes, donde los comandos se transmiten en el espacio de la tarea del entorno remoto. El método es validado para realizar telemanipulación hábil de objetos con un robot industrial. Por último, se introducen dos contribuciones en el campo de la manipulación robótica. Por un lado, se presenta un nuevo algoritmo de cinemática inversa, llamado método iterativo de desacoplamiento cinemático. Este método se ha desarrollado para resolver el problema cinemático inverso de un tipo de robot de seis grados de libertad donde una solución cerrada no está disponible. La eficacia del método se compara con métodos numéricos convencionales. Además, se ha diseñado una taxonomía robusta de agarres que permite controlar diferentes manos robóticas utilizando una correspondencia, basada en gestos, entre los espacios de trabajo de la mano humana y de la mano robótica. El gesto de la mano humana se identifica mediante la lectura de los movimientos relativos del índice, el pulgar y el dedo medio del usuario durante las primeras etapas del agarre. ABSTRACT Regardless of the availability of highly sophisticated techniques and ever increasing computing capabilities, the problems associated with robots interacting with unstructured environments remains an open challenge. Despite great advances in autonomous robotics, there are some situations where a humanin- the-loop is still required, such as, nuclear, space, subsea and robotic surgery operations. This is because the current technologies cannot reliably perform all kinds of task autonomously. This thesis presents methods for robot teleoperation strategies at different levels of abstraction ranging from supervisory control, where the operator gives high-level task actions, to bilateral teleoperation, where the commands take the form of low-level control inputs. These strategies contribute to improve the current human-robot interfaces specially in the case of slave robots deployed at large workspaces. First, an approach to perform supervisory teleoperation of humanoid robots is presented. The goal is to control ground robots capable of executing complex tasks in disaster relief environments under constrained communication links. This proposal incorporates autonomous behaviors that the operator can use to perform navigation and manipulation tasks which allow covering large human engineered areas of the remote environment. The experimental results demonstrate the efficiency of the proposed methods. Second, the use of cost-effective devices for guided telemanipulation is investigated. A case study involving a bimanual humanoid robot and an Inertial Measurement Unit (IMU) Motion Capture (MoCap) suit is introduced. Herein, it is corroborated how the adaptation capabilities offered by the human-in-the-loop factor can compensate for the lack of high-precision robotic systems. This work is the result of collaboration between researchers from the Harvard Biorobotics Laboratory and the Centre for Automation and Robotics UPM-CSIC. Thirdly, a new haptic rate-position controller is presented. This hybrid bilateral controller copes with the problems related to the teleoperation of a slave robot with large workspace using a small haptic device as master. Large workspaces can be covered by automatically switching between rate and position control modes. This haptic controller is ideal to couple kinematic dissimilar master-slave systems where the commands are transmitted in the task space of the remote environment. The method is validated to perform dexterous telemanipulation of objects with a robotic manipulator. Finally, two contributions for robotic manipulation are introduced. First, a new algorithm, the Iterative Kinematic Decoupling method, is presented. It is a numeric method developed to solve the Inverse Kinematics (IK) problem of a type of six-DoF robotic arms where a close-form solution is not available. The effectiveness of this IK method is compared against conventional numerical methods. Second, a robust grasp mapping has been conceived. It allows to control a wide range of different robotic hands using a gesture based correspondence between the human hand space and the robotic hand space. The human hand gesture is identified by reading the relative movements of the index, thumb and middle fingers of the user during the early stages of grasping.

A vision-based strategy for autonomous aerial refueling tasks

Autonomous aerial refueling is a key enabling technology for both manned and unmanned aircraft where extended flight duration or range are required. The results presented within this paper offer one potential vision-based sensing solution, together with a unique test environment. A hierarchical visual tracking algorithm based on direct methods is proposed and developed for the purposes of tracking a drogue during the capture stage of autonomous aerial refueling, and of estimating its 3D position. Intended to be applied in real time to a video stream from a single monocular camera mounted on the receiver aircraft, the algorithm is shown to be highly robust, and capable of tracking large, rapid drogue motions within the frame of reference. The proposed strategy has been tested using a complex robotic testbed and with actual flight hardware consisting of a full size probe and drogue. Results show that the vision tracking algorithm can detect and track the drogue at real-time frame rates of more than thirty frames per second, obtaining a robust position estimation even with strong motions and multiple occlusions of the drogue.

An Autonomous Engine for Services Configuration and Deployment.

The runtime management of the infrastructure providing service-based systems is a complex task, up to the point where manual operation struggles to be cost effective. As the functionality is provided by a set of dynamically composed distributed services, in order to achieve a management objective multiple operations have to be applied over the distributed elements of the managed infrastructure. Moreover, the manager must cope with the highly heterogeneous characteristics and management interfaces of the runtime resources. With this in mind, this paper proposes to support the configuration and deployment of services with an automated closed control loop. The automation is enabled by the definition of a generic information model, which captures all the information relevant to the management of the services with the same abstractions, describing the runtime elements, service dependencies, and business objectives. On top of that, a technique based on satisfiability is described which automatically diagnoses the state of the managed environment and obtains the required changes for correcting it (e.g., installation, service binding, update, or configuration). The results from a set of case studies extracted from the banking domain are provided to validate the feasibility of this proposa

Engineering an Ontology for Autonomous Systems - The OASys Ontology

This paper describes the development of an ontology for autonomous systems, as the initial stage of a research programe on autonomous systems’ engineering within a model-based control approach. The ontology aims at providing a unified conceptual framework for the autonomous systems’ stakeholders, from developers to software engineers. The modular ontology contains both generic and domain-specific concepts for autonomous systems description and engineering. The ontology serves as the basis in a methodology to obtain the autonomous system’s conceptual models. The objective is to obtain and to use these models as main input for the autonomous system’s model-based control system.

Amorphous piezoresistive and piezoelectric sensors for robotics applications

Ultrasonic transducers have often been used in the development of sensory systems for robotics applications. In most cases, these sensory systems are based on the determination of times of flight for signals from every transducer. In this work we have used piezoresistive and piezoelectric materials to measure the instant and position collision in metallic structures by using the difference of the times of propagation of an acoustic wave when it is produced over a ferromagnetic (iron, steel or another material) based structure. An immediate application of the proposed method is the detection and location of impacts over the metallic links of an industrial robot or the collision position in a metallic structure for an automated inspection

A Visual AGV-Urban Car using Fuzzy Control

The goal of the work described in this paper is to develop a visual line guided system for being used on-board an Autonomous Guided Vehicle (AGV) commercial car, controlling the steering and using just the visual information of a line painted below the car. In order to implement the control of the vehicle, a Fuzzy Logic controller has been implemented, that has to be robust against curvature changes and velocity changes. The only input information for the controller is the visual distance from the image center captured by a camera pointing downwards to the guiding line on the road, at a commercial frequency of 30Hz. The good performance of the controller has successfully been demonstrated in a real environment at urban velocities. The presented results demonstrate the capability of the Fuzzy controller to follow a circuit in urban environments without previous information about the path or any other information from additional sensors

Non-linear Control of an Autonomous Ground Vehicle

In this paper, in order to select a speed controller for a specific non-linear autonomous ground vehicle, proportional-integral-derivative (PID), Fuzzy, and linear quadratic regulator (LQR) controllers were designed. Here, in order to carry out the tuning of the above controllers, a multicomputer genetic algorithm (MGA) was designed. Then, the results of the MGA were used to parameterize the PID, Fuzzy and LQR controllers and to test them under laboratory conditions. Finally, a comparative analysis of the performance of the three controllers was conducted.

Fault Tolerance Analysis and Self-Healing Strategy of Autonomous, Evolvable Hardware Systems

This paper presents an analysis of the fault tolerance achieved by an autonomous, fully embedded evolvable hardware system, which uses a combination of partial dynamic reconfiguration and an evolutionary algorithm (EA). It demonstrates that the system may self-recover from both transient and cumulative permanent faults. This self-adaptive system, based on a 2D array of 16 (4×4) Processing Elements (PEs), is tested with an image filtering application. Results show that it may properly recover from faults in up to 3 PEs, that is, more than 18% cumulative permanent faults. Two fault models are used for testing purposes, at PE and CLB levels. Two self-healing strategies are also introduced, depending on whether fault diagnosis is available or not. They are based on scrubbing, fitness evaluation, dynamic partial reconfiguration and in-system evolutionary adaptation. Since most of these adaptability features are already available on the system for its normal operation, resource cost for self-healing is very low (only some code additions in the internal microprocessor core)

Autonomous vehicle control systems for safe crossroads

This article presents a cooperative manoeuvre among three dual mode cars – vehicles equipped with sensors and actuators, and that can be driven either manually or autonomously. One vehicle is driven autonomously and the other two are driven manually. The main objective is to test two decision algorithms for priority conflict resolution at intersections so that a vehicle autonomously driven can take their own decision about crossing an intersection mingling with manually driven cars without the need for infrastructure modifications. To do this, the system needs the position, speeds, and turning intentions of the rest of the cars involved in the manoeuvre. This information is acquired via communications, but other methods are also viable, such as artificial vision. The idea of the experiments was to adjust the speed of the manually driven vehicles to force a situation where all three vehicles arrive at an intersection at the same time.

Cartography for cooperative manoeuvres with autonomous land vehicles

This article presents a cartographic system to facilitate cooperative manoeuvres among autonomous vehicles in a well-known environment. The main objective is to design an extended cartographic system to help in the navigation of autonomous vehicles. This system has to allow the vehicles not only to access the reference points needed for navigation, but also noticeable information such as the location and type of traffic signals, the proximity to a crossing, the streets en route, etc. To do this, a hierarchical representation of the information has been chosen, where the information has been stored in two levels. The lower level contains the archives with the Universal Traverse Mercator (UTM) coordinates of the points that define the reference segments to follow. The upper level contains a directed graph with the relational database in which streets, crossings, roundabouts and other points of interest are represented. Using this new system it is possible to know when the vehicle approaches a crossing, what other paths arrive at that crossing, and, should there be other vehicles circulating on those paths and arriving at the crossing, which one has the highest priority. The data obtained from the cartographic system is used by the autonomous vehicles for cooperative manoeuvres.

Combining series elastic actuation and magneto-rheological damping for the control of agile locomotion

All-terrain robot locomotion is an active topic of research. Search and rescue maneuvers and exploratory missions could benefit from robots with the abilities of real animals. However, technological barriers exist to ultimately achieving the actuation system, which is able to meet the exigent requirements of these robots. This paper describes the locomotioncontrol of a leg prototype, designed and developed to make a quadruped walk dynamically while exhibiting compliant interaction with the environment. The actuation system of the leg is based on the hybrid use of series elasticity and magneto-rheological dampers, which provide variable compliance for natural-looking motion and improved interaction with the ground. The locomotioncontrol architecture has been proposed to exploit natural leg dynamics in order to improve energy efficiency. Results show that the controller achieves a significant reduction in energy consumption during the leg swing phase thanks to the exploitation of inherent leg dynamics. Added to this, experiments with the real leg prototype show that the combined use of series elasticity and magneto-rheologicaldamping at the knee provide a 20 % reduction in the energy wasted in braking the knee during its extension in the leg stance phase.

Response threshold models, stochastic learning automata and ant colony optimization-based decentralized self-coordination algorithms for heterogeneous multi-tasks distribution in multi-robot systems

In recent decades, there has been an increasing interest in systems comprised of several autonomous mobile robots, and as a result, there has been a substantial amount of development in the eld of Articial Intelligence, especially in Robotics. There are several studies in the literature by some researchers from the scientic community that focus on the creation of intelligent machines and devices capable to imitate the functions and movements of living beings. Multi-Robot Systems (MRS) can often deal with tasks that are dicult, if not impossible, to be accomplished by a single robot. In the context of MRS, one of the main challenges is the need to control, coordinate and synchronize the operation of multiple robots to perform a specic task. This requires the development of new strategies and methods which allow us to obtain the desired system behavior in a formal and concise way. This PhD thesis aims to study the coordination of multi-robot systems, in particular, addresses the problem of the distribution of heterogeneous multi-tasks. The main interest in these systems is to understand how from simple rules inspired by the division of labor in social insects, a group of robots can perform tasks in an organized and coordinated way. We are mainly interested on truly distributed or decentralized solutions in which the robots themselves, autonomously and in an individual manner, select a particular task so that all tasks are optimally distributed. In general, to perform the multi-tasks distribution among a team of robots, they have to synchronize their actions and exchange information. Under this approach we can speak of multi-tasks selection instead of multi-tasks assignment, which means, that the agents or robots select the tasks instead of being assigned a task by a central controller. The key element in these algorithms is the estimation ix of the stimuli and the adaptive update of the thresholds. This means that each robot performs this estimate locally depending on the load or the number of pending tasks to be performed. In addition, it is very interesting the evaluation of the results in function in each approach, comparing the results obtained by the introducing noise in the number of pending loads, with the purpose of simulate the robot's error in estimating the real number of pending tasks. The main contribution of this thesis can be found in the approach based on self-organization and division of labor in social insects. An experimental scenario for the coordination problem among multiple robots, the robustness of the approaches and the generation of dynamic tasks have been presented and discussed. The particular issues studied are: Threshold models: It presents the experiments conducted to test the response threshold model with the objective to analyze the system performance index, for the problem of the distribution of heterogeneous multitasks in multi-robot systems; also has been introduced additive noise in the number of pending loads and has been generated dynamic tasks over time. Learning automata methods: It describes the experiments to test the learning automata-based probabilistic algorithms. The approach was tested to evaluate the system performance index with additive noise and with dynamic tasks generation for the same problem of the distribution of heterogeneous multi-tasks in multi-robot systems. Ant colony optimization: The goal of the experiments presented is to test the ant colony optimization-based deterministic algorithms, to achieve the distribution of heterogeneous multi-tasks in multi-robot systems. In the experiments performed, the system performance index is evaluated by introducing additive noise and dynamic tasks generation over time.

Dimensional synthesis of a spherical parallel manipulator based on the evaluation of global performance indexes

In this work, the dimensional synthesis of a spherical Parallel Manipulator (PM) with a -1S kinematic chain is presented. The goal of the synthesis is to find a set of parameters that defines the PM with the best performance in terms of workspace capabilities, dexterity and isotropy. The PM is parametrized in terms of a reference element, and a non-directed search of these parameters is carried out. First, the inverse kinematics and instantaneous kinematics of the mechanism are presented. The latter is found using the screw theory formulation. An algorithm that explores a bounded set of parameters and determines the corresponding value of global indexes is presented. The concepts of a novel global performance index and a compound index are introduced. Simulation results are shown and discussed. The best PMs found in terms of each performance index evaluated are locally analyzed in terms of its workspace and local dexterity. The relationship between the performance of the PM and its parameters is discussed, and a prototype with the best performance in terms of the compound index is presented and analyzed.

Kinematic analysis of a novel 2-d.o.f. orientation device

This paper presents the development of a new parallel robot designed for helping with bone milling surgeries. The robot is a small modular wrist with 2 active degrees of freedom, and it is proposed to be used as an orientation device located at the end of a robotic arm designed for bone milling processes. A generic kinematic geometry is proposed for this device. This first article shows the developments on the workspace optimization and the analysis of the force field required to complete a reconstruction of the inferior jawbone. The singularities of the mechanism are analyzed, and the actuator selection is justified with the torque requirements and the study of the force space. The results obtained by the simulations allow building a first prototype using linear motors. Bone milling experiment video is shown as additional material.