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IEEE International Conference on robotics and Automation

作者： Morimoto, J Cheng, G Atkeson, CG Zeglin, G Department of Humanoid Robotics ATR Computational Neuroscience Labs. Japan Robotics Institute Carnegie Mellon University United States

ISBN: (纸本)0780382323

We propose a model-based reinforcement learning algorithm for biped walking in which the robot learns to appropriately place the swing leg. This decision is based on a learned model of the Poincare map of the periodic walking pattern. The model maps from a state at the middle of a step and foot placement to a state at next middle of a step. We also modify the desired walking cycle frequency based on online measurements. We present simulation results, and are currently implementing this approach on an actual biped robot.

关键词： Biped locomotion

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LEARNING to ACT from OBSERVATION and PRACTICE

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International Journal of humanoid robotics 2004年第4期1卷 585-611页

作者： Bentivegna, Darrin C. Atkeson, Christopher G. Ude, Aleš Cheng, Gordon ATR Computational Neuroscience Laboratories Department of Humanoid Robotics and Computational Neuroscience Kyoto619-0288 Japan Computational Brain Project ICORP Japan Science and Technology Agency Kyoto Japan Carnegie Mellon University Robotics Institute PittsburghPA United States Jozef Stefan Institute Department of Automatics Biocybernetics and Robotics Ljubljana Slovenia

We present a method for humanoid robots to quickly learn new dynamic tasks from observing others and from practice. Ways in which the robot can adapt to initial and also changing conditions are described. Agents are given domain knowledge in the form of task primitives. A key element of our approach is to break learning problems up into as many simple learning problems as possible. We present a case study of a humanoid robot learning to play air hockey. © 2004 World Scientific Publishing Company.

关键词： Anthropomorphic robots

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HAND-EYE COORDINATION THROUGH ENDPOINT CLOSED-LOOP and LEARNED ENDPOINT OPEN-LOOP VISUAL SERVO CONTROL

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International Journal of humanoid robotics 2005年第2期2卷 203-224页

作者： Gaskett, Chris Ude, Aleš Cheng, Gordon James Cook University School of Information Technology CairnsQLD Australia ATR Computational Neuroscience Laboratories Department of Humanoid Robotics and Computational Neuroscience 2-2-2 Hikaridai Seika-cho Soraku-gun Kyoto619-0288 Japan Computational Brain Project ICORP Japan Science and Technology Agency Kyoto Japan

We propose a hand-eye coordination system for a humanoid robot that supports bimanual reaching. The system combines endpoint closed-loop and open-loop visual servo control. The closed-loop component moves the eyes, head, arms, and torso, based on the position of the target and the robot's hands, as seen by the robot's head-mounted cameras. The open-loop component uses a motor-motor mapping that is learnt online to support movement when visual cues are not available. © 2005 World Scientific Publishing Company.

关键词： Self organizing maps

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A simple reinforcement learning algorithm for biped walking

A simple reinforcement learning algorithm for biped walking

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IEEE International Conference on robotics and Automation (ICRA)

作者： J. Morimoto G. Cheng C.G. Atkeson G. Zeglin Department of Humanoid Robotics and Computational Neuroscience ATR Computational Neuroscience Laboratories Japan The Robotics Institute Carnegie Mellon University USA

关键词： Learning Legged locomotion Frequency estimation Foot Timing Phase estimation humanoid robots Leg Humans Oscillators

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Compliant control of a hydraulic humanoid joint

Compliant control of a hydraulic humanoid joint

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IEEE-RAS International Conference on humanoid Robots

作者： Darrin C. Bentivegna Christopher G. Atkeson Jung-Yup Kim Robotics Institute Carnegie Mellon University Pittsburgh PA USA Department of Humanoid Robotics and Computational Neuroscience ATR Computational Neuroscience Laboratories Kyoto Japan

This paper presents an analysis of a hydraulic joint on a humanoid robot. Various controllers have been designed that allow the limb to have a range of characteristics such as being stiff or compliant.

关键词： Torque control Leg humanoid robots Hydraulic actuators Valves Legged locomotion Hip Servomechanisms Force sensors Velocity control

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Online gain switching algorithm for joint position control of a hydraulic humanoid robot

Online gain switching algorithm for joint position control o...

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IEEE-RAS International Conference on humanoid Robots

作者： Jung-Yup Kim Christopher G. Atkeson Jessica K. Hodgins Darrin C. Bentivegna Sung Ju Cho Robotics Institute Carnegie Mellon University Pittsburgh PA USA Department of Humanoid Robotics and Computational Neuroscience ATR Computational Neuroscience Laboratories Kyoto Japan

This paper proposes a gain switching algorithm for joint position control of a hydraulic humanoid robot. Accurate position control of the lower body is one of the basic requirements for robust balance and walking control. Joint position control is more difficult for hydraulic robots than it is for electric robots because of a slower actuator time constant and the back-drivability of hydraulic joints. Backdrivability causes external forces and torques to have a large effect on the position of the joints. External ground reaction forces therefore prevent a simple proportional-derivative (PD) controller from realizing accurate joint position control. We propose a state feedback controller for joint position control of the lower body, define three modes of state feedback gains, and switch the gains according to the zero moment point (ZMP) using linear interpolation. The performance of the algorithm is evaluated with a dynamic simulation of a hydraulic humanoid.

关键词： Position control humanoid robots Joints PD control State feedback Switches Robust control Legged locomotion Hydraulic actuators Force control

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Object recognition on humanoids with poveated vision

Object recognition on humanoids with poveated vision

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IEEE-RAS International Conference on humanoid Robots

作者： A. Ude G. Gheng Department of Automatics Joåâef Stefan Institute Ljubljana Slovenia Department of Humanoid Robotics and Computational Neuroscience ATR Computational Neuroscience Laboratories Kyoto Japan

Object recognition requires a robot to perform a number of nontrivial tasks such as finding objects of interest, directing its eyes towards the objects, pursuing them, and identifying the objects once they appear in the robot’s central vision. In this paper we describe a system that make use of foveated vision to solve the problem of object recognition on a humanoid robot. The system employs a biologically motivated object representation scheme based on Gabor kernel functions to represent multiple views of objects. We demonstrate how to utilize support vector machines to identify known objects in foveal images using this representation. A mechanism for visual search is integrated into the system to find a salient region and to place an object of interest in the field of view of foveal cameras. The framework also includes a control scheme for eye movements, which are directed using the results of attentive processing in peripheral images.

关键词： Object recognition Robot vision systems Cameras humanoid robots Eyes robotics and automation Computer vision Lenses Face detection Layout

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Active 3-D vision on a humanoid head

Active 3-D vision on a humanoid head

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International Conference on Advanced robotics (ICAR)

作者： Ales Ude Erhan Oztop Department of Automatics Biocybernetics and Robotics Jožef Stefan Institute Slovenia Department of Humanoid Robotics and Computational Neuroscience ATR Computational Neuroscience Laboratories Japan ICORP Computational Brain project Japan Science and Technology Agency Japan

In this paper we describe and experimentally evaluate how to model, control, and use the capabilities of a humanoid visual system with foveated vision. We present a computational process that can be utilized to identify and update the parameters of the robot's eyes under motion, which enables the use of 3D vision on an active humanoid head. We also derive the formulas expressing the geometry of our foveated vision setup. Based on these results we can actively control the eye gaze towards the potential regions of interest and analyze these areas using foveation and 3D vision processing. Experimental results showing the accuracy of the system are provided. The system has been demonstrated to be sufficiently accurate to realize grasping using active 3D vision.

关键词： Cameras Robot vision systems Computer vision Eyes humanoid robots Image resolution Humans Head Machine vision robotics and automation

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Learning from observation and from practice using behavioral primitives

Springer Tracts in Advanced Robotics

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Springer Tracts in Advanced robotics 2005年 15卷 551-560页

作者： Bentivegna, Darrin Cheng, Gordon Atkeson, Christopher ATR Computational Neuroscience Laboratories Department of Humanoid Robotics and Computational Neuroscience Kyoto Japan College of Computing Georgia Institute of Technology Atlanta GA United States Robotics Institute Carnegie Mellon University Pittsburgh PA United States

We describe a memory-based approach to learning how to select and provide subgoals for behavioral primitives, given an existing library of primitives. We demonstrate both learning from observation and learning from pr... 详细信息

关键词： Artificial intelligence

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2006 IEEE/RSJ International Conference on Intelligent Robots and Systems

作者： Darrin C. Bentivegna Christopher G. Atkeson Gordon Cheng Robotics Institute Carnegie Mellon University Pittsburgh PA USA Department of Humanoid Robotics and Computational Neuroscience ATR Computational Neuroscience Laboratories Kyoto Japan ICORP Japan Science and Technology Agency Kyoto Japan

This paper presents a case study of learning to select behavioral primitives and generate subgoals from observation and practice. Our approach uses local features to generalize across tasks and global features to learn from practice. We demonstrate this approach applied to the marble maze task. Our robot uses local features to initially learn primitive selection and subgoal generation policies from observing a teacher maneuver a marble through a maze. The robot then uses this information as it tries to traverse another maze, and refines the information during learning from practice

关键词： Intelligent robots Orbital robotics humanoid robots Educational robots Hardware Libraries USA Councils Laboratories Education Navigation

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