Cooperative localization for mobile agents: a recursive decentralized algorithm based on Kalman filter decoupling

We consider cooperative localization technique for mobile agents with communication and computation capabilities. We start by provide and overview of different decentralization strategies in the literature, with special focus on how these algorithms maintain an account of intrinsic correlations between state estimate of team members. Then, we present a novel decentralized cooperative localization algorithm that is a decentralized implementation of a centralized Extended Kalman Filter for cooperative localization. In this algorithm, instead of propagating cross-covariance terms, each agent propagates new intermediate local variables that can be used in an update stage to create the required propagated cross-covariance terms. Whenever there is a relative measurement in the network, the algorithm declares the agent making this measurement as the interim master. By acquiring information from the interim landmark, the agent the relative measurement is taken from, the interim master can calculate and broadcast a set of intermediate variables which each robot can then use to update its estimates to match that of a centralized Extended Kalman Filter for cooperative localization. Once an update is done, no further communication is needed until the next relative measurement

A contribution to the incorporation of sociability and creativity skills to computers and robots

This dissertation contains the research and work completed by the PhD candidate on the incorporation of sociability and creativity skills to computers and robots. Both skills can be directly related with empathy, which is the ability to understand and share the feelings of another. In this form, this research can be contextualized in the framework of recent developments towards the achievement of empathy machines. The first challenge at hands refers to designing pioneering techniques based on the use of social robots to improve user experience interacting with them. In particular, research focus is on eliminating or minimizing pain and anxiety as well as loneliness and stress of long-term hospitalized child patients. This challenge is approached by developing a cloud-based robotics architecture to effectively develop complex tasks related to hospitalized children assistance. More specifically, a multiagent learning system is introduced based on a combination of machine learning and cloud computing using low-cost robots (Innvo labs's Pleo rb). Moreover, a wireless communication system is also developed for the Pleo robot in order to help the health professional who conducts therapy with the child, monitoring, understanding, and controlling Pleo behavior at any moment. As a second challenge, a new formulation of the concept of creativity is proposed in order to empower computers with. Based on previous well established theories from Boden and Wiggins, this thesis redefines the formal mechanism of exploratory and transformational creativity in a way which facilitates the computational implementation of these mechanisms in Creativity Support Systems. The proposed formalization is applied and validated on two real cases: the first, about chocolate designing, in which a novel and flavorful combination of chocolate and fruit is generated. The second case is about the composition of a single voice tune of reel using ABC notation

A contribution to the incorporation of sociability and creativity skills to computers and robots

This dissertation contains the research and work completed by the PhD candidate on the incorporation of sociability and creativity skills to computers and robots. Both skills can be directly related with empathy, which is the ability to understand and share the feelings of another. In this form, this research can be contextualized in the framework of recent developments towards the achievement of empathy machines. The first challenge at hands refers to designing pioneering techniques based on the use of social robots to improve user experience interacting with them. In particular, research focus is on eliminating or minimizing pain and anxiety as well as loneliness and stress of long-term hospitalized child patients. This challenge is approached by developing a cloud-based robotics architecture to effectively develop complex tasks related to hospitalized children assistance. More specifically, a multiagent learning system is introduced based on a combination of machine learning and cloud computing using low-cost robots (Innvo labs's Pleo rb). Moreover, a wireless communication system is also developed for the Pleo robot in order to help the health professional who conducts therapy with the child, monitoring, understanding, and controlling Pleo behavior at any moment. As a second challenge, a new formulation of the concept of creativity is proposed in order to empower computers with. Based on previous well established theories from Boden and Wiggins, this thesis redefines the formal mechanism of exploratory and transformational creativity in a way which facilitates the computational implementation of these mechanisms in Creativity Support Systems. The proposed formalization is applied and validated on two real cases: the first, about chocolate designing, in which a novel and flavorful combination of chocolate and fruit is generated. The second case is about the composition of a single voice tune of reel using ABC notation.Postprint (published version

Automatic supervision of temperature, humidity, and luminance with an Assistant Personal Robot

Smart environments and Ambient Intelligence (AmI) technologies are defining the future society where energy optimization and intelligent management are essential for a sustainable advance. Mobile robotics is also making an important contribution to this advance with the integration of sensors and intelligent processing algorithms. This paper presents the application of an Assistant Personal Robot (APR) as an autonomous agent for temperature, humidity, and luminance supervision in human-frequented areas. The robot multiagent capabilities allow gathering sensor information while exploring or performing specific tasks and then verifying human comfortability levels. The proposed methodology creates information maps with the distribution of temperature, humidity, and luminance and interprets such information in terms of comfort and warns about corrective actuations if required

Robotic control based on the human nervous system

This article presents a model of robotic control system inspired by the human neuroregulatory system. This model allows the application of functional and organizational principles of biological systems to robotic systems. It also proposes appropriate technologies to implement this proposal, in particular the services. To illustrate the proposal, we implemented a control system for mobile robots in dynamic open environments, demonstrating the viability of both the model and the technologies chosen for implementation

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

The role of trust in proactive conversational assistants

Humans and machines harmoniously collaborating and bene ting from each other is a long lasting dream for researchers in robotics and arti cial intelligence. An important feature of ef cient and rewarding cooperation is the ability to assume possible problematic situations and act in advance to prevent negative outcomes. This concept of assistance is known under the term proactivity. In this article, we investigate the development and implementation of proactive dialogues for fostering a trustworthy human-computer relationship and providing adequate and timely assistance. Here, we make several contributions. A formalisation of proactive dialogue in conversational assistants is provided. The formalisation forms a framework for integrating proactive dialogue in conversational applications. Additionally, we present a study showing the relations between proactive dialogue actions and several aspects of the perceived trustworthiness of a system as well as effects on the user experience. The results of the experiments provide signi cant contributions to the line of proactive dialogue research. Particularly, we provide insights on the effects of proactive dialogue on the human-computer trust relationship and dependencies between proactive dialogue and user specific and situational characteristics