Multi-Modal Human-Machine Communication for Instructing Robot Grasping Tasks

A major challenge for the realization of intelligent robots is to supply them with cognitive abilities in order to allow ordinary users to program them easily and intuitively. One way of such programming is teaching work tasks by interactive demonstration. To make this effective and convenient for the user, the machine must be capable to establish a common focus of attention and be able to use and integrate spoken instructions, visual perceptions, and non-verbal clues like gestural commands. We report progress in building a hybrid architecture that combines statistical methods, neural networks, and finite state machines into an integrated system for instructing grasping tasks by man-machine interaction. The system combines the GRAVIS-robot for visual attention and gestural instruction with an intelligent interface for speech recognition and linguistic interpretation, and an modality fusion module to allow multi-modal task-oriented man-machine communication with respect to dextrous robot manipulation of objects.Comment: 7 pages, 8 figure

Graphite immobilisation in glass composite materials

Irradiated graphite is a problematic nuclear waste stream and currently raises significant concern worldwide in identifying its long-term disposal route. This thesis describes the use of glass materials for the immobilisation of irradiated graphite prepared by microwave, conventional and sparks plasma sintering methods. Several potential glass compositions namely iron phosphate, aluminoborosilicate, calcium aluminosilicate, alkali borosilicate and obsidian were considered for the immobilisation of various loadings of graphite simulating irradiated graphite. The properties of the samples produced using different processing methods are compared selectively. An investigation of microwave processing using an iron phosphate glass composition revealed that full reaction of the raw materials and formation of a glass melt occurs with consequent removal of porosity at 8 minutes microwave processing. When graphite is present, iron phosphate crystalline phases are formed with much higher levels of residual porosity of up to 43 % than in the samples prepared using conventional sintering under argon. It is found that graphite reacts with the microwave field when in powder form but this reaction is minimised when the graphite is incorporated into a pellet, and that the graphite also impedes sintering of the glass. Mössbauer spectroscopy indicates that reduction of iron occurs with concomitant graphite oxidation. The production of graphite-glass samples using various powdered glass compositions by conventional sintering method still resulted in high porosity with an average of 6-17 % for graphite loadings of 20-25 wt%. Due to the use of pre-made glasses and controlled sintering parameters, the loss of graphite from the total mass is reduced compared to the microwaved samples; the average mass loss is < 0.8 %. The complication of iron oxidation and reduction is present in all the iron containing base glasses considered and this increases the total porosity of the graphite-glass samples. It is concluded that the presence of iron in the raw materials or base glasses as an encapsulation media for the immobilisation of the irradiated graphite waste is not advisable. The production of glass and graphite-glass samples based calcium aluminosilicate composition by spark plasma sintering method is found highly suitable for the immobilisation of irradiated graphite wastes. The advantages of the method includes short processing time i.e. < 40 minutes, improved sintering transport mechanisms, limited graphite oxidation, low porosity (1-4 %) and acceptable tensile strength (2-7 MPa). The most promising samples prepared using spark plasma sintering method were loaded with 30-50 wt% graphite

The ITALK project : A developmental robotics approach to the study of individual, social, and linguistic learning

This is the peer reviewed version of the following article: Frank Broz et al, “The ITALK Project: A Developmental Robotics Approach to the Study of Individual, Social, and Linguistic Learning”, Topics in Cognitive Science, Vol 6(3): 534-544, June 2014, which has been published in final form at doi: http://dx.doi.org/10.1111/tops.12099 This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving." Copyright © 2014 Cognitive Science Society, Inc.This article presents results from a multidisciplinary research project on the integration and transfer of language knowledge into robots as an empirical paradigm for the study of language development in both humans and humanoid robots. Within the framework of human linguistic and cognitive development, we focus on how three central types of learning interact and co-develop: individual learning about one's own embodiment and the environment, social learning (learning from others), and learning of linguistic capability. Our primary concern is how these capabilities can scaffold each other's development in a continuous feedback cycle as their interactions yield increasingly sophisticated competencies in the agent's capacity to interact with others and manipulate its world. Experimental results are summarized in relation to milestones in human linguistic and cognitive development and show that the mutual scaffolding of social learning, individual learning, and linguistic capabilities creates the context, conditions, and requisites for learning in each domain. Challenges and insights identified as a result of this research program are discussed with regard to possible and actual contributions to cognitive science and language ontogeny. In conclusion, directions for future work are suggested that continue to develop this approach toward an integrated framework for understanding these mutually scaffolding processes as a basis for language development in humans and robots.Peer reviewe

Learning and Composing Primitive Skills for Dual-Arm Manipulation

In an attempt to confer robots with complex manipulation capabilities, dual-arm anthropomorphic systems have become an important research topic in the robotics community. Most approaches in the literature rely upon a great understanding of the dynamics underlying the system's behaviour and yet offer limited autonomous generalisation capabilities. To address these limitations, this work proposes a modelisation for dual-arm manipulators based on dynamic movement primitives laying in two orthogonal spaces. The modularity and learning capabilities of this model are leveraged to formulate a novel end-to-end learning-based framework which (i) learns a library of primitive skills from human demonstrations, and (ii) composes such knowledge simultaneously and sequentially to confront novel scenarios. The feasibility of the proposal is evaluated by teaching the iCub humanoid the basic skills to succeed on simulated dual-arm pick-and-place tasks. The results suggest the learning and generalisation capabilities of the proposed framework extend to autonomously conduct undemonstrated dual-arm manipulation tasks.Comment: Annual Conference Towards Autonomous Robotic Systems (TAROS19