Knowledge Representation for Robots through Human-Robot Interaction

The representation of the knowledge needed by a robot to perform complex tasks is restricted by the limitations of perception. One possible way of overcoming this situation and designing "knowledgeable" robots is to rely on the interaction with the user. We propose a multi-modal interaction framework that allows to effectively acquire knowledge about the environment where the robot operates. In particular, in this paper we present a rich representation framework that can be automatically built from the metric map annotated with the indications provided by the user. Such a representation, allows then the robot to ground complex referential expressions for motion commands and to devise topological navigation plans to achieve the target locations.Comment: Knowledge Representation and Reasoning in Robotics Workshop at ICLP 201

Pathway to Future Symbiotic Creativity

This report presents a comprehensive view of our vision on the development path of the human-machine symbiotic art creation. We propose a classification of the creative system with a hierarchy of 5 classes, showing the pathway of creativity evolving from a mimic-human artist (Turing Artists) to a Machine artist in its own right. We begin with an overview of the limitations of the Turing Artists then focus on the top two-level systems, Machine Artists, emphasizing machine-human communication in art creation. In art creation, it is necessary for machines to understand humans' mental states, including desires, appreciation, and emotions, humans also need to understand machines' creative capabilities and limitations. The rapid development of immersive environment and further evolution into the new concept of metaverse enable symbiotic art creation through unprecedented flexibility of bi-directional communication between artists and art manifestation environments. By examining the latest sensor and XR technologies, we illustrate the novel way for art data collection to constitute the base of a new form of human-machine bidirectional communication and understanding in art creation. Based on such communication and understanding mechanisms, we propose a novel framework for building future Machine artists, which comes with the philosophy that a human-compatible AI system should be based on the "human-in-the-loop" principle rather than the traditional "end-to-end" dogma. By proposing a new form of inverse reinforcement learning model, we outline the platform design of machine artists, demonstrate its functions and showcase some examples of technologies we have developed. We also provide a systematic exposition of the ecosystem for AI-based symbiotic art form and community with an economic model built on NFT technology. Ethical issues for the development of machine artists are also discussed

User-centered design of a dynamic-autonomy remote interaction concept for manipulation-capable robots to assist elderly people in the home

In this article, we describe the development of a human-robot interaction concept for service robots to assist elderly people in the home with physical tasks. Our approach is based on the insight that robots are not yet able to handle all tasks autonomously with sufficient reliability in the complex and heterogeneous environments of private homes. We therefore employ remote human operators to assist on tasks a robot cannot handle completely autonomously. Our development methodology was user-centric and iterative, with six user studies carried out at various stages involving a total of 241 participants. The concept is under implementation on the Care-O-bot 3 robotic platform. The main contributions of this article are (1) the results of a survey in form of a ranking of the demands of elderly people and informal caregivers for a range of 25 robot services, (2) the results of an ethnography investigating the suitability of emergency teleassistance and telemedical centers for incorporating robotic teleassistance, and (3) a user-validated human-robot interaction concept with three user roles and corresponding three user interfaces designed as a solution to the problem of engineering reliable service robots for home environments

Head motion tracking in 3D space for drivers

Ce travail présente un système de vision par ordinateur capable de faire un suivi du mouvement en 3D de la tête d’une personne dans le cadre de la conduite automobile. Ce système de vision par ordinateur a été conçu pour faire partie d'un système intégré d’analyse du comportement des conducteurs tout en remplaçant des équipements et des accessoires coûteux, qui sont utilisés pour faire le suivi du mouvement de la tête, mais sont souvent encombrants pour le conducteur. Le fonctionnement du système est divisé en quatre étapes : l'acquisition d'images, la détection de la tête, l’extraction des traits faciaux, la détection de ces traits faciaux et la reconstruction 3D des traits faciaux qui sont suivis. Premièrement, dans l'étape d'acquisition d'images, deux caméras monochromes synchronisées sont employées pour former un système stéréoscopique qui facilitera plus tard la reconstruction 3D de la tête. Deuxièmement, la tête du conducteur est détectée pour diminuer la dimension de l’espace de recherche. Troisièmement, après avoir obtenu une paire d’images de deux caméras, l'étape d'extraction des traits faciaux suit tout en combinant les algorithmes de traitement d'images et la géométrie épipolaire pour effectuer le suivi des traits faciaux qui, dans notre cas, sont les deux yeux et le bout du nez du conducteur. Quatrièmement, dans une étape de détection des traits faciaux, les résultats 2D du suivi sont consolidés par la combinaison d'algorithmes de réseau de neurones et la géométrie du visage humain dans le but de filtrer les mauvais résultats. Enfin, dans la dernière étape, le modèle 3D de la tête est reconstruit grâce aux résultats 2D du suivi et ceux du calibrage stéréoscopique des caméras. En outre, on détermine les mesures 3D selon les six axes de mouvement connus sous le nom de degrés de liberté de la tête (longitudinal, vertical, latéral, roulis, tangage et lacet). La validation des résultats est effectuée en exécutant nos algorithmes sur des vidéos préenregistrés des conducteurs utilisant un simulateur de conduite afin d'obtenir des mesures 3D avec notre système et par la suite, à les comparer et les valider plus tard avec des mesures 3D fournies par un dispositif pour le suivi de mouvement installé sur la tête du conducteur.This work presents a computer vision module capable of tracking the head motion in 3D space for drivers. This computer vision module was designed to be part of an integrated system to analyze the behaviour of the drivers by replacing costly equipments and accessories that track the head of a driver but are often cumbersome for the user. The vision module operates in five stages: image acquisition, head detection, facial features extraction, facial features detection, and 3D reconstruction of the facial features that are being tracked. Firstly, in the image acquisition stage, two synchronized monochromatic cameras are used to set up a stereoscopic system that will later make the 3D reconstruction of the head simpler. Secondly the driver’s head is detected to reduce the size of the search space for finding facial features. Thirdly, after obtaining a pair of images from the two cameras, the facial features extraction stage follows by combining image processing algorithms and epipolar geometry to track the chosen features that, in our case, consist of the two eyes and the tip of the nose. Fourthly, in a detection stage, the 2D tracking results are consolidated by combining a neural network algorithm and the geometry of the human face to discriminate erroneous results. Finally, in the last stage, the 3D model of the head is reconstructed from the 2D tracking results (e.g. tracking performed in each image independently) and calibration of the stereo pair. In addition 3D measurements according to the six axes of motion known as degrees of freedom of the head (longitudinal, vertical and lateral, roll, pitch and yaw) are obtained. The validation of the results is carried out by running our algorithms on pre-recorded video sequences of drivers using a driving simulator in order to obtain 3D measurements to be compared later with the 3D measurements provided by a motion tracking device installed on the driver’s head

Open-Source TIG-Based Metal 3D-Printing

Metal 3-D printing has been relegated to high-cost proprietary high-resolution systems and low-resolution low-cost metal inert gas (MIG) systems. In order to provide a path to high-resolution, low-cost, metal 3-D printing, this manuscript proposes a new open source metal 3-D printer design based around a low-cost tungsten inert gas (TIG) welder coupled to a commercial open source self replicating rapid prototyper. Optimal printing parameters for the machine are acquired using a novel computational intelligence software. TIG has many advantages over MIG, such as having a low heat input, clean beads, and the potential for both high-resolution prints as well as insitu alloying of complex geometries. The design can be adapted to most RepRap-class systems and has a basic yet powerful free and open source software (FOSS) package for the characterization of the 3-D printer. This system can be used for fabricating custom metal scientific components and tools, near net-shape structural metal component rapid prototyping, adapting and depositing on existing metal structures, and is deployable for in-field prototyping for appropriate technology applications

Agricultural Swarm Robotics with Distributed Sensing

To prove a symbiotic relationship of robotics and distributed sensing, the team designed and built a set of sensor nodes to work in tandem with a mobile robot, mesh network, and server database. This relationship concept was proven by creating and implementing this platform to log climate data for a field of crops

BWIBots: A platform for bridging the gap between AI and human–robot interaction research

Recent progress in both AI and robotics have enabled the development of general purpose robot platforms that are capable of executing a wide variety of complex, temporally extended service tasks in open environments. This article introduces a novel, custom-designed multi-robot platform for research on AI, robotics, and especially human–robot interaction for service robots. Called BWIBots, the robots were designed as a part of the Building-Wide Intelligence (BWI) project at the University of Texas at Austin. The article begins with a description of, and justification for, the hardware and software design decisions underlying the BWIBots, with the aim of informing the design of such platforms in the future. It then proceeds to present an overview of various research contributions that have enabled the BWIBots to better (a) execute action sequences to complete user requests, (b) efficiently ask questions to resolve user requests, (c) understand human commands given in natural language, and (d) understand human intention from afar. The article concludes with a look forward towards future research opportunities and applications enabled by the BWIBot platform

Body-Borne Computers as Extensions of Self

The opportunities for wearable technologies go well beyond always-available information displays or health sensing devices. The concept of the cyborg introduced by Clynes and Kline, along with works in various fields of research and the arts, offers a vision of what technology integrated with the body can offer. This paper identifies different categories of research aimed at augmenting humans. The paper specifically focuses on three areas of augmentation of the human body and its sensorimotor capabilities: physical morphology, skin display, and somatosensory extension. We discuss how such digital extensions relate to the malleable nature of our self-image. We argue that body-borne devices are no longer simply functional apparatus, but offer a direct interplay with the mind. Finally, we also showcase some of our own projects in this area and shed light on future challenges