14,218 research outputs found

    Humanoid Motion Description Language

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    In this paper we propose a description language for specifying motions for humanoid robots and for allowing humanoid robots to acquire motor skills. Locomotion greatly increases our ability to interact with our environments, which in turn increases our mental abilities. This principle also applies to humanoid robots. However, there are great difficulties to specify humanoid motions and to represent motor skills, which in most cases require four-dimensional space representations. We propose a representation framework that includes the following attributes: motion description layers, egocentric reference system, progressive quantized refinement, and automatic constraint satisfaction. We also outline strategies for acquiring new motor skills by learning from trial and error, macro approach, and programming. Then, we outline the development of a new humanoid motion description language called Cybele

    "Sticky Hands": learning and generalization for cooperative physical interactions with a humanoid robot

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    "Sticky Hands" is a physical game for two people involving gentle contact with the hands. The aim is to develop relaxed and elegant motion together, achieve physical sensitivity-improving reactions, and experience an interaction at an intimate yet comfortable level for spiritual development and physical relaxation. We developed a control system for a humanoid robot allowing it to play Sticky Hands with a human partner. We present a real implementation including a physical system, robot control, and a motion learning algorithm based on a generalizable intelligent system capable itself of generalizing observed trajectories' translation, orientation, scale and velocity to new data, operating with scalable speed and storage efficiency bounds, and coping with contact trajectories that evolve over time. Our robot control is capable of physical cooperation in a force domain, using minimal sensor input. We analyze robot-human interaction and relate characteristics of our motion learning algorithm with recorded motion profiles. We discuss our results in the context of realistic motion generation and present a theoretical discussion of stylistic and affective motion generation based on, and motivating cross-disciplinary research in computer graphics, human motion production and motion perception

    The Iterative Development of the Humanoid Robot Kaspar: An Assistive Robot for Children with Autism

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    This paper gives an overview of the design and development of the humanoid robot Kaspar. Since the first Kaspar robot was developed in 2005, the robotic platform has undergone continuous development driven by the needs of users and technological advancements enabling the integration of new features. We discuss in detail the iterative development of Kaspar’s design and clearly explain the rational of each development, which has been based on the user requirements as well as our years of experience in robot assisted therapy for children with autism, particularly focusing on how the developments benefit the children we work with. Further to this, we discuss the role and benefits of robotic autonomy on both children and therapist along with the progress that we have made on the Kaspar robot’s autonomy towards achieving a semi-autonomous child-robot interaction in a real world setting.Peer reviewe

    Exploring the Design Space of Robot Appearance and Behavior in an Attention-Seeking Living Room Scenario for a Robot Companion

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    This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.---- Copyright IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. --DOI : 10.1109/ALIFE.2007.36781

    Using humanoid robots to study human behavior

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    Our understanding of human behavior advances as our humanoid robotics work progresses-and vice versa. This team's work focuses on trajectory formation and planning, learning from demonstration, oculomotor control and interactive behaviors. They are programming robotic behavior based on how we humans “program” behavior in-or train-each other
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