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This book focuses on two issues related to human figures: realtime dynamics computation and interactive motion generation. In spite of the growing interest in human figures as both physical robots and virtual characters, standard algorithms and tools for their kinematics and dynamics computation have not been investigated very much. "Simulating and Generating Motions of Human Figures" presents original algorithms to simulate, analyze, generate and control motions of human figures, all focusing on realtime and interactive computation. The book provides both practical methods for contact/collision simulation essential for the simulation of humanoid robots and virtual characters and a general framework for online, interactive motion generation of human figures based on the dynamics simulation algorithms.
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)
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.
The area of simulated human figures is an active research area in computer graphics, and Norman Badler's group at the University of Pennsylvania is one of the leaders in the field. This book summarizes the state of the art in simulating human figures, discusses many of the interesting application areas, and makes some assumptions and predictions about where the field is going.
The 20 research papers in this volume demonstrate novel models and concepts in animation and graphics simulation. Special emphasis is given on innovative approaches to Modelling Human Motion, Models of Collision Detection and Perception, Facial Animation and Communication, Specific Animation Models, Realistic Rendering for Animation, and Behavioral Animation.
Humans always wanted to go faster and higher than their own legs could carry them. This led them to invent numerous types of vehicles to move fast over land, water and air. As training how to handle such vehicles and testing new developments can be dangerous and costly, vehicle motion simulators were invented. Motion-based simulators in particular, combine visual and physical motion cues to provide occupants with a feeling of being in the real vehicle. While visual cues are generally not limited in amplitude, physical cues certainly are, due to the limited simulator motion space. A motion cueing algorithm (MCA) is used to map the vehicle motions onto the simulator motion space. This mapping inherently creates mismatches between the visual and physical motion cues. Due to imperfections in the human perceptual system, not all visual/physical cueing mismatches are perceived. However, if a mismatch is perceived, it can impair the simulation realism and even cause simulator sickness. For MCA design, a good understanding of when mismatches are perceived, and ways to prevent these from occurring, are therefore essential. In this thesis a data-driven approach, using continuous subjective measures of the time-varying Perceived Motion Incongruence (PMI), is adopted. PMI in this case refers to the effect that perceived mismatches between visual and physical motion cues have on the resulting simulator realism. The main goal of this thesis was to develop an MCA-independent off-line prediction method for time-varying PMI during vehicle motion simulation, with the aim of improving motion cueing quality. To this end, a complete roadmap, describing how to measure and model PMI and how to apply such models to predict and minimize PMI in motion simulations is presented. Results from several human-in-the-loop experiments are used to demonstrate the potential of this novel approach.
The rapid introduction of sophisticated computers, services, telecommunications systems, and manufacturing systems has caused a major shift in the way people use and work with technology. It is not surprising that computer-aided modeling has emerged as a promising method for ensuring products meet the requirements of the consumer. The Handbook of D
Principles of Flight Simulation is a comprehensive guide to flight simulator design, covering the modelling, algorithms and software which underpin flight simulation. The book covers the mathematical modelling and software which underpin flight simulation. The detailed equations of motion used to model aircraft dynamics are developed and then applied to the simulation of flight control systems and navigation systems. Real-time computer graphics algorithms are developed to implement aircraft displays and visual systems, covering OpenGL and OpenSceneGraph. The book also covers techniques used in motion platform development, the design of instructor stations and validation and qualification of simulator systems. An exceptional feature of Principles of Flight Simulation is access to a complete suite of software (www.wiley.com/go/allerton) to enable experienced engineers to develop their own flight simulator – something that should be well within the capability of many university engineering departments and research organisations. Based on C code modules from an actual flight simulator developed by the author, along with lecture material from lecture series given by the author at Cranfield University and the University of Sheffield Brings together mathematical modeling, computer graphics, real-time software, flight control systems, avionics and simulator validation into one of the faster growing application areas in engineering Features full colour plates of images and photographs. Principles of Flight Simulation will appeal to senior and postgraduate students of system dynamics, flight control systems, avionics and computer graphics, as well as engineers in related disciplines covering mechanical, electrical and computer systems engineering needing to develop simulation facilities.