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Many data-driven animation techniques are capable of producing high quality motions of human characters. Few techniques, however, are capable of generating motions that are consistent with physically simulated environments. Physically simulated characters, in contrast, are automatically consistent with the environment, but their motions are often unnatural because they are difficult to control. We present a model-predictive controller that yields natural motions by guiding simulated humans toward real motion data. During simulation, the predictive component of the controller solves a quadratic program to compute the forces for a short window of time into the future. These forces are then applied by a low-gain proportional-derivative component, which makes minor adjustments until the next planning cycle. The controller is fast enough for interactive systems such as games and training simulations. It requires no precomputation and little manual tuning. The controller is resilient to mismatches between the character dynamics and the input motion, which allows it to track motion capture data even where the real dynamics are not known precisely. The same principled formulation can generate natural walks, runs, and jumps in a number of different physically simulated surroundings.
Simulate realistic human motion in a virtual world with an optimization-based approach to motion prediction. With this approach, motion is governed by human performance measures, such as speed and energy, which act as objective functions to be optimized. Constraints on joint torques and angles are imposed quite easily. Predicting motion in this way allows one to use avatars to study how and why humans move the way they do, given specific scenarios. It also enables avatars to react to infinitely many scenarios with substantial autonomy. With this approach it is possible to predict dynamic motion without having to integrate equations of motion -- rather than solving equations of motion, this approach solves for a continuous time-dependent curve characterizing joint variables (also called joint profiles) for every degree of freedom. Introduces rigorous mathematical methods for digital human modelling and simulation Focuses on understanding and representing spatial relationships (3D) of biomechanics Develops an innovative optimization-based approach to predicting human movement Extensively illustrated with 3D images of simulated human motion (full color in the ebook version)
This volume is concerned with digital human modeling. The utility of this area of research is to aid the design of systems that are benefitted from reducing the need for physical prototyping and incorporating ergonomics and human factors earlier in design processes. Digital human models are representations of some aspects of a human that can be ins
The model-based investigation of motions of anthropomorphic systems is an important interdisciplinary research topic involving specialists from many fields such as Robotics, Biomechanics, Physiology, Orthopedics, Psychology, Neurosciences, Sports, Computer Graphics and Applied Mathematics. This book presents a study of basic locomotion forms such as walking and running is of particular interest due to the high demand on dynamic coordination, actuator efficiency and balance control. Mathematical models and numerical simulation and optimization techniques are explained, in combination with experimental data, which can help to better understand the basic underlying mechanisms of these motions and to improve them. Example topics treated in this book are Modeling techniques for anthropomorphic bipedal walking systems Optimized walking motions for different objective functions Identification of objective functions from measurements Simulation and optimization approaches for humanoid robots Biologically inspired control algorithms for bipedal walking Generation and deformation of natural walking in computer graphics Imitation of human motions on humanoids Emotional body language during walking Simulation of biologically inspired actuators for bipedal walking machines Modeling and simulation techniques for the development of prostheses Functional electrical stimulation of walking.
The advent of augmented reality technologies used to assist human operators in complex manipulative operations—has brought an urgency to research into the modeling and training of human skills in Virtual Environments. However, modeling a specific act still represents a challenge in cognitive science. The same applies for the control of humanoid robots and the replication of skilled behavior of avatars in Virtual Environments. Skill Training in Multimodal Virtual Environments presents the scientific background, research outcomes, engineering developments, and evaluation studies conducted during the five years (2006-2011) of the project SKILLS–Multimodal Interfaces for Capturing and Transfer of Skill, funded by the European Commission under its 6th Framework Programme for Research and Technological Development. The SKILLS project evaluated how to exploit robotics and virtual environment technologies for the training of specific skills. This book details the novel approach used in the study to cope with skill acquisition, setting aside the mainstream assumptions of common computer-assisted training simulators. It explores how the SKILLS approach generated new training scenarios that allow users to practice new experiences in the performance of the devised task. Using a carefully designed approach that balances science with practicality, the book explores how virtual and augmented reality systems can be designed to address the skill transfer and training in different application contexts. The application of the same roadmap to skills originating from domains such as sports, rehabilitation, industrial environment, and surgery sets this book apart. It demonstrates how technology-oriented training conditions can yield better results than more traditional training conditions.
The two volume set LNCS 5358 and LNCS 5359 constitutes the refereed proceedings of the 4th International Symposium on Visual Computing, ISVC 2008, held in Las Vegas, NV, USA, in December 2008. The 102 revised full papers and 70 poster papers presented together with 56 full and 8 poster papers of 8 special tracks were carefully reviewed and selected from more than 340 submissions. The papers are organized in topical sections on computer graphics, visualization, shape/recognition, video analysis and event recognition, virtual reality, reconstruction, motion, face/gesture, and computer vision applications. The 8 additional special tracks address issues such as object recognition, real-time vision algorithm implementation and application, computational bioimaging and visualization, discrete and computational geometry, soft computing in image processing and computer vision, visualization and simulation on immersive display devices, analysis and visualization of biomedical visual data, as well as image analysis for remote sensing data.
This book provides state-of-the-art scientific and engineering research findings and developments in the area of mobile robotics and associated support technologies. The book contains peer reviewed articles presented at the CLAWAR 2008 conference. Robots are no longer confined to industrial manufacturing environments with a great deal of interest being invested in the use of robots outside the factory environment. The CLAWAR conference series, established as a high profile international event, acts as a platform for the dissemination of research and development findings and supports such a trend to address the current interest in mobile robotics in meeting the needs of mankind in various sectors of the society. These include personal care, public health, and services in the domestic, public and industrial environments. The editors of the book have extensive research experience and publications in the area of robotics specifically in mobile robotics, and their experience is reflected in the careful editing of the contents in the book.
We consider a new approach to digital human simulation, using Model Predictive Control (MPC). This approach permits a virtual human to react online to unanticipated disturbances that occur in the course of performing a task. In particular, we predict the motion of a virtual human in response to two different types of real world disturbances: impulsive and sustained. This stands in contrast to prior approaches where all such disturbances need to be known a priori and the optimal reactions must be computed off line. We validate this approach using a planar 3 degrees of freedom serial chain mechanism to imitate the human upper limb. The response of the virtual human upper limb to various inputs and external disturbances is determined by solving the Equations of Motion (EOM). The control input is determined by the MPC Controller using only the current and the desired states of the system. MPC replaces the closed loop optimization problem with an open loop optimization allowing the ease of implementation of control law. Results presented in this thesis show that the proposed controller can produce physically realistic adaptive simulations of a planar upper limb of digital human in presence of impulsive and sustained disturbances.
Encyclopedia of Computer Graphics and Games (ECGG) is a unique reference resource tailored to meet the needs of research and applications for industry professionals and academic communities worldwide. The ECGG covers the history, technologies, and trends of computer graphics and games. Editor Newton Lee, Institute for Education, Research, and Scholarships, Los Angeles, CA, USA Academic Co-Chairs Shlomo Dubnov, Department of Music and Computer Science and Engineering, University of California San Diego, San Diego, CA, USA Patrick C. K. Hung, University of Ontario Institute of Technology, Oshawa, ON, Canada Jaci Lee Lederman, Vincennes University, Vincennes, IN, USA Industry Co-Chairs Shuichi Kurabayashi, Cygames, Inc. & Keio University, Kanagawa, Japan Xiaomao Wu, Gritworld GmbH, Frankfurt am Main, Hessen, Germany Editorial Board Members Leigh Achterbosch, School of Science, Engineering, IT and Physical Sciences, Federation University Australia Mt Helen, Ballarat, VIC, Australia Ramazan S. Aygun, Department of Computer Science, Kennesaw State University, Marietta, GA, USA Barbaros Bostan, BUG Game Lab, Bahçeşehir University (BAU), Istanbul, Turkey Anthony L. Brooks, Aalborg University, Aalborg, Denmark Guven Catak, BUG Game Lab, Bahçeşehir University (BAU), Istanbul, Turkey Alvin Kok Chuen Chan, Cambridge Corporate University, Lucerne, Switzerland Anirban Chowdhury, Department of User Experience and Interaction Design, School of Design (SoD), University of Petroleum and Energy Studies (UPES), Dehradun, Uttarakhand, India Saverio Debernardis, Dipartimento di Meccanica, Matematica e Management, Politecnico di Bari, Bari, Italy Abdennour El Rhalibi, Liverpool John Moores University, Liverpool, UK Stefano Ferretti, Department of Computer Science and Engineering, University of Bologna, Bologna, Italy Han Hu, School of Information and Electronics, Beijing Institute of Technology, Beijing, China Ms. Susan Johnston, Select Services Films Inc., Los Angeles, CA, USA Chris Joslin, Carleton University, Ottawa, Canada Sicilia Ferreira Judice, Department of Computer Science, University of Calgary, Calgary, Canada Hoshang Kolivand, Department Computer Science, Faculty of Engineering and Technology, Liverpool John Moores University, Liverpool, UK Dario Maggiorini, Department of Computer Science, University of Milan, Milan, Italy Tim McGraw, Purdue University, West Lafayette, IN, USA George Papagiannakis, ORamaVR S.A., Heraklion, Greece; FORTH-ICS, Heraklion Greece University of Crete, Heraklion, Greece Florian Richoux, Nantes Atlantic Computer Science Laboratory (LINA), Université de Nantes, Nantes, France Andrea Sanna, Dipartimento di Automatica e Informatica, Politecnico di Torino, Turin, Italy Yann Savoye, Institut fur Informatik, Innsbruck University, Innsbruck, Austria Sercan Şengün, Wonsook Kim School of Art, Illinois State University, Normal, IL, USA Ruck Thawonmas, Ritsumeikan University, Shiga, Japan Vinesh Thiruchelvam, Asia Pacific University of Technology & Innovation, Kuala Lumpur, Malaysia Rojin Vishkaie, Amazon, Seattle, WA, USA Duncan A. H. Williams, Digital Creativity Labs, Department of Computer Science, University of York, York, UK Sai-Keung Wong, National Chiao Tung University, Hsinchu, Taiwan Editorial Board Intern Sam Romershausen, Vincennes University, Vincennes, IN, USA