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IEEE International Conference on robotics and Automation (ICRA)

作者： Jim Mainprice Rafi Hayne Dmitry Berenson Autonomous Motion Department Max-Planck-Institute for Intelligent Systems Tbingen Germany Robotics Engineering Program Worcester Polytechnic Institute Worcester MA

To enable safe and efficient human-robot collaboration in shared workspaces, it is important for the robot to predict how a human will move when performing a task. While predicting human motion for tasks not known a priori is very challenging, we argue that single-arm reaching motions for known tasks in collaborative settings (which are especially relevant for manufacturing) are indeed predictable. Two hypotheses underlie our approach for predicting such motions: First, that the trajectory the human performs is optimal with respect to an unknown cost function, and second, that human adaptation to their partner's motion can be captured well through iterative replanning with the above cost function. The key to our approach is thus to learn a cost function which “explains” the motion of the human. To do this, we gather example trajectories from two participants performing a collaborative assembly task using motion capture. We then use Inverse Optimal Control to learn a cost function from these trajectories. Finally, we predict a human's motion for a given task by iteratively replanning a trajectory for a 23 DoF human kinematic model using the STOMP algorithm with the learned cost function in the presence of a moving collaborator. Our results suggest that our method outperforms baseline methods and generalizes well for tasks similar to those that were demonstrated.

关键词： Trajectory Collaboration Cost function Planning Optimal control Prediction algorithms Hidden Markov models

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Gene expression imputation across multiple brain regions provides insights into schizophrenia risk (vol 51, pg 659, 2019)

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NATURE GENETICS 2019年第6期51卷 1068-1068页

作者： Huckins, Laura M. Dobbyn, Amanda Ruderfer, Douglas M. Hoffman, Gabriel Wang, Weiqing Pardinas, Antonio F. Rajagopal, Veera M. Als, Thomas D. Nguyen, Hoang T. Girdhar, Kiran Boocock, James Roussos, Panos Fromer, Menachem Kramer, Robin Domenici, Enrico Gamazon, Eric R. Purcell, Shaun Demontis, Ditte Borglum, Anders D. Walters, James T. R. O'Donovan, Michael C. Sullivan, Patrick Owen, Michael J. Devlin, Bernie Sieberts, Solveig K. Cox, Nancy J. Im, Hae Kyung Sklar, Pamela Stahl, Eli A. Pamela Sklar Division of Psychiatric Genomics Icahn School of Medicine at Mount Sinai New York NY USA Department of Genetics and Genomics Icahn School of Medicine at Mount Sinai New York NY USA Department of Psychiatry Icahn School of Medicine at Mount Sinai New York NY USA Icahn Institute for Genomics and Multiscale Biology Icahn School of Medicine at Mount Sinai New York NY USA Vanderbilt University Medical Center Nashville TN USA MRC Centre for Neuropsychiatric Genetics and Genomics Cardiff University Cardiff UK Department of Biomedicine Aarhus University Aarhus Denmark The Lundbeck Foundation Initiative for Integrative Psychiatric Research iPSYCH Denmark Center for Integrative Sequencing Aarhus University Aarhus Denmark Department of Human Genetics David Geffen School of Medicine University of California Los Angeles Los Angeles CA USA Human Brain Collection Core National Institute of Mental Health Bethesda MD USA Laboratory of Neurogenomic Biomarkers Centre for Integrative Biology (CIBIO) University of Trento Trento Italy Clare Hall University of Cambridge Cambridge UK University of North Carolina at Chapel Hill Chapel Hill NC USA Karolinska Institutet Stockholm Sweden Department of Psychiatry University of Pittsburgh Pittsburgh PA USA Systems Biology Sage Bionetworks Seattle WA USA Section of Genetic Medicine Department of Medicine University of Chicago Chicago IL USA Integrated Technology Research Laboratories Pharmaceutical Research Division Takeda Pharmaceutical Company Limited Fujisawa Japan Neuropsychiatry Section Department of Psychiatry Perelman School of Medicine University of Pennsylvania Philadelphia PA USA Neuropsychiatric Signaling Program Department of Psychiatry Perelman School of Medicine University of Pennsylvania Philadelphia PA USA Psychiatry JJ Peters Virginia Medical Center Bronx NY USA Department of Neuroscience Icahn School of Medicine at Mount Sinai New York New York NY USA Friedman Brain Institute

Transcriptomic imputation approaches combine eQTL reference panels with large-scale genotype data in order to test associations between disease and gene expression. These genic associations could elucidate signals in complex genome-wide association study (GWAS) loci and may disentangle the role of different tissues in disease development. We used the largest eQTL reference panel for the dorso-lateral prefrontal cortex (DLPFC) to create a set of gene expression predictors and demonstrate their utility. We applied DLPFC and 12 GTEx-brain predictors to 40,299 schizophrenia cases and 65,264 matched controls for a large transcriptomic imputation study of schizophrenia. We identified 413 genic associations across 13 brain regions. Stepwise conditioning identified 67 non-MHC genes, of which 14 did not fall within previous GWAS loci. We identified 36 significantly enriched pathways, including hexosaminidase-A deficiency, and multiple porphyric disorder pathways. We investigated developmental expression patterns among the 67 non-MHC genes and identified specific groups of pre- and postnatal expression.

关键词： Gene expression Genome-wide association studies Schizophrenia Transcriptomics

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Explicit vs. Tacit leadership in influencing the behavior of swarms

Explicit vs. Tacit leadership in influencing the behavior of...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Saman Amirpour Amraii Phillip Walker Michael Lewis Nilanjan Chakraborty Katia Sycara School of Information Sciences and Intelligent Systems Program University of Pittsburgh Pittsburgh PA USA Robotics Institute Carnegie Mellon University Pittsburgh PA USA

Many researchers have employed some form of teleoperated leader to influence a robotic swarm; however, the way in which this influence is conveyed has not been well studied. Some researchers employ designated leaders that are known to be leaders by other members of the swarm and hence followed. Others do not impose a leader/follower distinction on the swarm's algorithms and instead choose to influence the swarm indirectly through controlling one or more of its members. Because the robustness of swarm behavior arises from its many distributed interactions, influence through designated leaders might render it susceptible to noise or disrupt its coherence by overriding these mechanisms. Conversely, limiting human influence to indirect control through the local effects of a leader might prove too sluggish to allow effective human control. This paper compares leader-based methods of each type, designated as Tacit leadership via consensus (no explicit leader/follower distinction) and Explicit leadership via flooding (influence propagating from leader takes precedence). These methods were compared in simulation and in human experiments finding that explicit leadership led to faster convergence in simulation and better performance in the experiments. Effects of noise were slightly more pronounced for Explicit leaders and cohesion slightly poorer.

关键词： Conferences Robots Automation

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Studying direct and indirect human influence on consensus in swarms

Studying direct and indirect human influence on consensus in...

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2012 AAAI Fall Symposium

作者： Amraii, Saman Amirpour Chakraborty, Nilanjan Lewis, Michael Intelligent Systems Program University of Pittsburgh Pittsburgh PA 15260 United States Robotics Institute Carnegie Mellon University Pittsburgh PA 15213 United States School of Information Sciences University of Pittsburgh Pittsburgh PA 15260 United States

Many cooperative control problems ranging from formation following, to rendezvous to flocking can be expressed as consensus problems. The ability of an operator to influence the development of consensus within a swarm therefore provides a basic test of the quality of human-swarm interaction (HSI). Two plausible approaches are : Direct- dictate a desired value to swarm members or Indirect- control or influence one or more swarm members relying on existing control laws to propagate that influence. Both approaches have been followed by HSI researchers. The Indirect case uses standard consensus methods where the operator exerts influence over a few robots and then the swarm reaches a consensus based on its intrinsic rules. The Direct method corresponds to flooding in which the operator directly sends the intention to a subset of the swarm and the command then propagates through the remainder of the swarm as a privileged message. In this paper we compare these two methods regarding their convergence time and properties in noisy and noiseless conditions with static and dynamic graphs. We have found that average consensus method (indirect control) converges much slower than flooding (direct) method but it has more noise tolerance in comparison with simple flooding algorithms. Also, we have found that the convergence time of the consensus method behaves erratically when the graph's connectivity (Fiedler value) is high. Copyright © 2012, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Floods

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Vision-based corridor path search of a mobile robot

Vision-based corridor path search of a mobile robot

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International Conference on Control, Automation and systems ( ICCAS)

作者： Yeoun-Jae Kim Joon-Yong Lee Majed S. Aldosari Mazin S. Altokhais Ju-Jang Lee Robotics Program KAIST Daejeon South Korea Department of Electrical Engineering KAIST Daejeon South Korea National Robotics & Intelligent Systems Center KACST Riyadh Saudi Arabia

In this paper, We made an algorithm for a mobile robot to determine direction normal to the wall with two cameras in an indoor environment without any direction-notification marks. Furthermore, with this direction determination ability, made a method with which a mobile robot can navigate and search through an indoor corridor path without any predefined map information is made. the direction determination scheme uses Hough transform and horizontal line search. While the path search algorithm uses SIFT(Scale-Invariant Feature Transformation), 3D reconstruction and binary search tree algorithm. In the direction determination stage, the mobile robot detects lines in the image and detects horizontal lines to determine the normal to the wall direction. After the direction determination stage is completed, the robot determines the corridor path range through SIFT, RANSAC algorithm, and 3D reconstruction, and finally navigates through its pathway. The direction determination and navigation stage constitutes the binary search tree algorithm. After searching through all its pathway in the indoor environment, the robot returns to its original position with various corridor position information.

关键词： Mobile robots Robot vision systems Cameras Navigation Transforms

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Autonomous driving manoeuvres in urban road traffic environment: a study on roundabouts

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IFAC Proceedings Volumes 2011年第1期44卷 13795-13800页

作者： Joshué Pérez Vicente Milanés Teresa de Pedro Ljubo Vlacic AUTOPIA program Centre for Automation and Robotics (CAR) University Polytechnic of Madrid (UPM) – Spanish National Research Council (CSIC) Madrid Spain Intelligent Control Systems Laboratory Griffith University Brisbane Australia

Abstract The highway and urban traffic safety has significantly been improved thanks to advanced development of intelligent Transportation systems technologies. However, some driving aspects have remained outside of this evolution or they are still in the development stage. Autonomous vehicle performance on roundabouts is one of these. In this paper, a simple and practical approach for the driverless control on roundabouts is described. Firstly, a description of a path planning is explained. Finally, a new concept for lateral control on roundabouts is introduced, taking into account entrances, exits and lane changes inside the roundabouts. The experiments have been tested in a 3D simulator that emulates the behaviour of driverless vehicle from the real world, – Cybercars. The results are promising, and leave the door open for future implementation in real vehicles.

关键词： Lane keeping autonomous vehicles roundabouts digital map intelligent Transportation systems (ITS)

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Model-based estimation of active knee stiffness

Model-based estimation of active knee stiffness

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IEEE International Conference on Rehabilitation robotics (ICORR)

作者： Serge Pfeifer Michael Hardegger Heike Vallery Renate List Mauro Foresti Robert Riener Eric J. Perreault Sensory-Motor Systems Laboratory Institute of Robotics and Intelligent Systems ETH Zurich Zurich Switzerland Sensory-Motor Systems Lab Institute of Robotics and Intelligent Systems ETH Zurich Zurich Switzerland & Spinal Cord Injury Center Medical Faculty Balgrist University Hospital Zurich Switzerland Institute for Biomechanics ETH Zurich Zurich Switzerland Institute for Surgical Technology & Biomechanics University of Bern Bern Switzerland Department of Biomed. Eng. and Department of Phys. Med. and Rehab. Northwestern University Chicago IL USA Sensory Motor Performance Program Rehabilitation Institute of Chicago Chicago IL USA

Knee joint impedance varies substantially during physiological gait. Quantifying this modulation is critical for the design of transfemoral prostheses that aim to mimic physiological limb behavior. Conventional methods for quantifying joint impedance typically involve perturbing the joint in a controlled manner, and describing impedance as the dynamic relationship between applied perturbations and corresponding joint torques. These experimental techniques, however, are difficult to apply during locomotion without impeding natural movements. In this paper, we propose a method to estimate the elastic component of knee joint impedance that depends on muscle activation, often referred to as active knee stiffness. The method estimates stiffness using a musculoskeletal model of the leg and a model for activation-dependent short-range muscle stiffness. Muscle forces are estimated from measurements including limb kinematics, kinetics and muscle electromyograms. For isometric validation, we compare model estimates to measurements involving joint perturbations; measured stiffness is 17% lower than model estimates for extension, and 42% lower for flexion torques. We show that sensitivity of stiffness estimates to common approaches for estimating muscle force is small in isometric conditions. We also make initial estimates of how knee stiffness is modulated during gait, illustrating how this approach may be used to obtain parameters relevant to the design of transfemoral prostheses.

关键词： Muscles Knee Joints Torque Force Load modeling Electromyography

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The Third International Conference on human-robot interaction

The Third International Conference on human-robot interactio...

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作者： Fong, Terry Dautenhahn, Kerstin Scheutz, Matthias Demiris, Yiannis Intelligent Robotics Group NASA Ames Research Center Department of Artificial Intelligence School of Computer Science University of Herfordshire Herfordshire United Kingdom Adaptive Systems Research Group University of Herfordshire Herfordshire United Kingdom Department of Cognitive Science Computer Science and Informatics Cognitive Science Program Indiana University Bloomington IN United States Intelligent Robotics Team Department of Electrical Engineering Imperial College London London United Kingdom

The third international conference on Human-Robot Interaction (HRI-2008) was held in Amsterdam, The Netherlands, March 12-15, 2008. The theme of HRI-2008, "living with robots," highlights the importance of the technical and social issues underlying human-robot interaction with companion and assistive robots for long-term use in everyday life and work activities. More than 250 researchers, practitioners, and exhibitors attended the conference, and many more contributed to the conference as authors or reviewers. HRI-2009 will be held in San Diego, California, from March 11-13, 2009. Copyright © 2008, Association for the Advancement of Artificial Intelligence. All rights reserved.

关键词： Human robot interaction

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HERMIES-III - A STEP TOWARD AUTONOMOUS MOBILITY, MANIPULATION AND PERCEPTION

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ROBOTICA 1990年第1期8卷 7-12页

作者： WEISBIN, CR BURKS, BL EINSTEIN, JR FEEZELL, RR MANGES, WW THOMPSON, DH Oak Ridge National Laboratory Robotics and Intelligent Systems Program Oak Ridge TN 37831–6364 (USA)

HERMIES-III is an autonomous robot comprised of a seven degree-of-freedom (DOF) manipulator designed for human scale tasks, a laser range finder, a sonar array, an omnidirectional wheel-driven chassis, multiple cameras, and a dual computer system containing a 16-node hypercube expandable to 128 nodes. The current experimental program involves performance of human-scale tasks (e.g., valve manipulation, use of tools), integration of a dexterous manipulator and platform motion in geometrically complex environments, and effective use of multiple cooperating robots (HERMIES-IIB and HERMIES-III). The environment in which the robots operate has been designed to include multiple valves, pipes, meters, obstacles on the floor, valves occluded from view, and multiple paths of differing navigation complexity. The ongoing research program supports the development of autonomous capability for HERMIES-IIB and III to perform complex navigation and manipulation under time constraints, while dealing with imprecise sensory information.

关键词： Autonomous mobility HERMIES-III Multi-sensory perception Human scale manipulative tasks

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REAL-TIME CONTROL - A SIGNIFICANT TEST OF AI TECHNOLOGIES - INTRODUCTION

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IEEE EXPERT-intelligent systems & THEIR APPLICATIONS 1987年第4期2卷 16-17页

作者： WEISBIN, CR Robotics and Intelligent Systems Program Oak Ridge National Laboratory PO Box X Oak Ridge TN 37831-6364.

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