Robot learning of everyday object manipulations via human demonstration

We deal with the problem of teaching a robot to manipulate everyday objects through human demonstration. We first design a task descriptor which encapsulates important elements of a task. The design originates from observations that manipulations involved in many everyday object tasks can be considered as a series of sequential rotations and translations, which we call manipulation primitives. We then propose a method that enables a robot to decompose a demonstrated task into sequential manipulation primitives and construct a task descriptor. We also show how to transfer a task descriptor learned from one object to similar objects. In the end, we argue that this framework is highly generic. Particularly, it can be used to construct a robot task database that serves as a manipulation knowledge base for a robot to succeed in manipulating everyday objects

Robot learning of everyday object manipulations via human demonstration

We deal with the problem of teaching a robot to manipulate everyday objects through human demonstration. We first design a task descriptor which encapsulates important elements of a task. The design originates from observations that manipulations involved in many everyday object tasks can be considered as a series of sequential rotations and translations, which we call manipulation primitives. We then propose a method that enables a robot to decompose a demonstrated task into sequential manipulation primitives and construct a task descriptor. We also show how to transfer a task descriptor learned from one object to similar objects. In the end, we argue that this framework is highly generic. Particularly, it can be used to construct a robot task database that serves as a manipulation knowledge base for a robot to succeed in manipulating everyday objects

Robot Learning with Task-Parameterized Generative Models

Task-parameterized models provide a representation of movement/behavior that can adapt to a set of task parameters describing the current situation encountered by the robot, such as location of objects or landmarks in its workspace. This paper gives an overview of the task-parameterized Gaussian mixture model (TP-GMM) introduced in previous publications, and introduces a number of extensions and ongoing challenges required to move the approach toward unconstrained environments. In particular, it discusses its generalization capability and the handling of movements with a high number of degrees of freedom. It then shows that the method is not restricted to movements in task space, but that it can also be exploited to handle constraints in joint space, including priority constraints

Bureau of Mines publications and articles, 1992-1993 (with subject and author index)

The U.S. Bureau of Mines (USBM) was established in the public interest to conclude inquiries and scientific and technologic investigations on mining and the preparation, treatment, and utilization of mineral substances; to promote health and safety in the mineral industries; to conserve material resources and prevent their waste; to further economic development; to increaseee efficiency in the mining, metallurgical, quarrying, and other mineral industries; and to inquire into the economic conditions affecting those industries. The organic act of the Bureau, as amended by Congress and approved February 25, 1913, made it the province and duty of the U.S. Bureau of Mines to "disseminate information concerning these subjects in such manner as will best carry out the purposes of this Act."In accordance with this directive, USBM reports the findings of its research and investigations in its own series of publications and also in articles that appear in scientific, technical, and trade journals; in proceedings of conventions and seminars; in reference books; and in other non-USBM publications. The number of these reports, the wide range of subjects they cover, and the variety of mediums in which they appear make this kind of list both necessary and valuable.This edition describes reports and articles published during calendar years 1992 and 1993. It supplements the 50-year list of Bureau publications from July 1, 1910, to January 1, 19602 ; and these 5-year lists of publications and articles: from January 1, 1965, to December 31, 1969 from January 1, 1970, to December 31, 1974, from January 1, 1975, to December 31, 197 , from January 1, 1980, to December 31,1984, and from January 1, 1985, to December 31, 1989.ISBN 0-16-045065-

Aerospace medicine and biology: A continuing bibliography with indexes (supplement 287)

This bibliography lists 346 reports, articles and other documents introduced into the NASA scientific and technical information system in July 1986

Technology 2001: The Second National Technology Transfer Conference and Exposition, volume 2

Proceedings of the workshop are presented. The mission of the conference was to transfer advanced technologies developed by the Federal government, its contractors, and other high-tech organizations to U.S. industries for their use in developing new or improved products and processes. Volume two presents papers on the following topics: materials science, robotics, test and measurement, advanced manufacturing, artificial intelligence, biotechnology, electronics, and software engineering

Adaptive sensorimotor peripersonal space representation and motor learning for a humanoid robot

This thesis presents possible computational mechanisms by which a humanoid robot can develop a coherent representation of the space within its reach (its peripersonal space), and use it to control its movements. Those mechanisms are inspired by current theories of peripersonal space representation and motor control in humans, targeting a cross-fertilization between robotics on one side, and cognitive science on the other side. This research addresses the issue of adaptivity the sensorimotor level, at the control level and at the level of simple task learning. First, this work considers the concept of body schema and suggests a computational translation of this concept, appropriate for controlling a humanoid robot. This model of the body schema is adaptive and evolves as a result of the robot sensory experience. It suggests new avenues for understanding various psychophysical and neuropsychological phenomenons of human peripersonal space representation such as adaptation to distorted vision and tool use, fake limbs experiments, body-part centered receptive fields, and multimodal neurons. Second, it is shown how the motor modality can be added to the body schema. The suggested controller is inspired by the dynamical system theory of motor control and allows the robot to simultaneously and robustly control its limbs in joint angles space and in end-effector location space. This amounts to controlling the robot in both proprioceptive and visual modalities. This multimodal control can benefit from the advantages offered by each modality and is better than traditional robotic controllers in several respects. It offers a simple and elegant solution to the singularity and joint limit avoidance problems and can be seen as a generalization of the Damped Least Square approach to robot control. The controller exhibits several properties of human reaching movements, such as quasi-straight hand paths and bell-shaped velocity profiles and non-equifinality. In a third step, the motor modalities is endowed with a statistical learning mechanism, based on Gaussian Mixture Models, that enables the humanoid to learn motor primitives from demonstrations. The robot is thus able to learn simple manipulation tasks and generalize them to various context, in a way that is robust to perturbations occurring during task execution. In addition to simulation results, the whole model has been implemented and validated on two humanoid robots, the Hoap3 and the iCub, enabling them to learn their arm and head geometries, perform reaching movements, adapt to unknown tools, and visual distortions, and learn simple manipulation tasks in a smooth, robust and adaptive way. Finally, this work hints at possible computational interpretations of the concepts of body schema, motor perception and motor primitives

Patient centric intervention for children with high functioning autism spectrum disorder. Can ICT solutions improve the state of the art ?

In my PhD research we developed an integrated technological platform for the acquisition of neurophysiologic signals in a semi-naturalistic setting where children are free to move around, play with different objects and interact with the examiner. The interaction with the examiner rather than with a screen is another very important feature of the present research, and allows recreating a more real situation with social interactions and cues. In this paradigm, we can assume that the signals acquired from the brain and the autonomic system, are much more similar to what is generated while the child interacts in common life situations. This setting, with a relatively simple technical implementation, can be considered as one step towards a more behaviorally driven analysis of neurophysiologic activity. Within the context of a pilot open trial, we showed the feasibility of the technological platform applied to the classical intervention solutions for the autism. We found that (1) the platform was useful during both children-therapist interaction at hospital as well as children-parents interaction at home, (2) tailored intervention was compatible with at home use and non-professional therapist/parents. Going back to the title of my thesis: 'Can ICT solution improve the state-of-the-art ?' the answer could be: 'Yes it can be an useful support for a skilled professional in the field of autis