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Technical Paper

Real-Time Obstacle Avoidance for Posture Prediction

2009-06-09
2009-01-2305
Collision avoidance in digital human modeling is critical for design and analysis, especially when there is interaction between the avatar and his/her environment. This paper describes a new algorithm for obstacle avoidance with optimization-based posture prediction. This new approach is motivated by a need for decreased computational time and increased fidelity for modeling and analysis of collision avoidance tasks. Posture prediction is run in an iterative loop while conducting collision detection to dynamically update collision avoidance constraints. It is shown that this approach is substantially faster than the basic method involving a fixed number of sphere-based avoidance constraints with a single optimization/posture-prediction run. The method is demonstrated using an upper-body virtual human model in a cab setting.
Technical Paper

Multiple User Defined End-Effectors with Shared Memory Communication for Posture Prediction

2008-06-17
2008-01-1922
Inverse Kinematics on a human model combined with optimization provides a powerful tool to predict realistic human postures. A human posture prediction tool brings up the need for greater flexibility for the user, as well as efficient computation performance. This paper demonstrates new methods that were developed for the application of digital human simulation as a software package by allowing for any number of user specified end-effectors and increasing communication efficiency for posture prediction. The posture prediction package for the digital human, Santos™, uses optimization constrained by end-effectors on the body with targets in the environment, along with variable cost functions that are minimized, to solve for all joint angles in a human body. This results in realistic human postures which can be used to create optimal designs for things that humans can physically interact with.
Journal Article

General Biped Motion and Balance of a Human Model

2008-06-17
2008-01-1932
We propose an algorithm of predicting dynamic biped motions of Santos™ human model. An alternative and efficient formulation of the Zero-Moment Point (ZMP) for dynamic balance and the approximated ground reaction forces/moments are derived from the resultant reaction loads, which includes the gravity, the externally applied loads, and the inertia. The optimization problem is formulated to address the redundancy of the human task, where the general biped and the task-specific constraints are imposed depending on the task requirements. The proposed method is fully predictive and generates physically feasible human-like motions from scratch without any input reference from motion capture or animation. The resulting generated motions demonstrate how a human reacts effectively to different external load conditions in performing a given task by showing realistic features of cause and effect.
Technical Paper

A Musculoskeletal Model of the Upper Limb for Real Time Interaction

2007-06-12
2007-01-2488
With the ever-increasing power of real time graphics and computational ability of desktop computers, the desire for a real-time simulation of the musculoskeletal system has become more pronounced. It is important that this simulation is realistic, interactive, runs in real time, and looks realistic, especially in our climate of Hollywood special-effects and stunning video games. An effective simulation of the musculoskeletal system hinges on three key features: accurate modeling of kinematic movement, realistic modeling of the muscle attachment points, and determining the direction of the forces applied at the points. By taking known information about the musculoskeletal system and applying it in a real time environment, we have created such a model of the human arm. This model includes realistic constraints on the joints and real-time wrapping algorithms for muscle action lines.
Technical Paper

Validation Methodology Development for Predicted Posture

2007-06-12
2007-01-2467
As predictive capabilities advance and human-model fidelity increases, so must validation of such predictions and models. However, subjective validation is sufficient only as an initial indicator; thorough, systematic studies must be conducted as well. Thus, the purpose of this paper is to validate postures that are determined using single-objective optimization (SOO) and multi-objective optimization (MOO), as applied to the virtual human Santos™. In addition, a general methodology and tools for posture-prediction validation are presented. We find that using MOO provides improvement over SOO, and the results are realistic from both a subjective and objective perspective.
Technical Paper

Optimization-Based Dynamic Motion Simulation and Energy Expenditure Prediction for a Digital Human

2005-06-14
2005-01-2717
This paper presents an optimization-based algorithm for simulating the dynamic motion of a digital human. We also formulate the metabolic energy expenditure during the motion, which is calculated within our algorithm. This algorithm is implemented and applied to Santos™, an avatar developed at The University of Iowa. Santos™ is a part of a virtual environment for conducting digital human analysis consisting of posture prediction, motion prediction, and physiology studies. This paper demonstrates our dynamic motion algorithm within the Santos™ virtual environment. Mathematical evaluations of human performance are essential to any effort to compare various ergonomic designs. In fact, the human factors design process can be formulated as an optimization problem that maximizes human performance. In particular, an optimal design must be found while taking into consideration the effects of different motions and hand loads corresponding to a number of tasks.
Technical Paper

Santos™: A New Generation of Virtual Humans

2005-04-11
2005-01-1407
Presented in this paper is an on-going project to develop a new generation of virtual human models that are highly realistic in terms of appearance, movement, and feedback (evaluation of the human body during task execution). Santos™ is an avatar that exhibits extensive modeling and simulation capabilities. It is an anatomically correct human model with more than 100 degrees of freedom. Santos™ resides in a virtual environment and can conduct human-factors analysis. This analysis entails, among other things, posture prediction, motion prediction, gait analysis, reach envelope analysis, and ergonomics studies. There are essentially three stages to developing virtual humans: (1) basic human modeling (representing how a human functions independently), (2) input functionality (awareness and analysis of the human’s environment), and (3) intelligent reaction to input (memory, reasoning, etc.). This paper addresses the first stage.
Technical Paper

Motion Prediction and Inverse Dynamics for Human Upper Extremities

2005-04-11
2005-01-1408
Santos™, a digital human avatar developed at The University of Iowa, exhibits extensive modeling and simulation capabilities. Santos™ is a part of a virtual environment for conducting human factors analysis consisting of posture prediction, motion prediction, and ergonomics studies. This paper presents part of the functionality in the Santos™ virtual environment, which is an optimization-based algorithm for simulating dynamic motion of Santos™. The joint torque and muscle power during the motion are also calculated within the algorithm. Mathematical cost functions that evaluate human performance are essential to any effort that would evaluate and compare various ergonomic designs. It is widely accepted that the ergonomic design process is actually an optimization problem with many design variables. This effort is basically a task-based approach that believes humans assume different postures and exert different forces to accomplish different tasks.
Technical Paper

Virtual Environment for Digital Human Simulation

2004-06-15
2004-01-2172
A general methodology and associated computational algorithm for predicting realistic postures of digital humans (mannequins) in a virtual environment is presented. The basic plot for this effort is a task-based approach, where we believe that humans assume different postures for different tasks. The underlying problem is characterized by the calculation (or prediction) of the joint displacements of the human body in such a way to accomplish a specified task. In this work, we have not limited the number of degrees of freedom associated with the model. Each task has been defined by a number of human performance measures that are mathematically represented by cost functions that evaluate to a real number. Cost functions are then optimized, i.e., minimized or maximized subject to a number of constraints. The problem is formulated as a multi-objective optimization algorithm where one or more cost functions are considered as objective functions that drive the model to a solution.
Technical Paper

Layout Design using an Optimization-Based Human Energy Consumption Formulation

2004-06-15
2004-01-2175
An optimization-based method for layout design (also called equipment layout) is presented that is based upon kinetic functions also introduced in this paper. The layout problem is defined by the method whereby positions of target points are specified in the environment surrounding a human. The problem is of importance to ergonomists, vehicle/cockpit packaging engineers, designers of manufacturing assembly lines, and designers concerned with the placement of lever, knobs, and controls in the reachable workspace of a human, but also to users of digital human modeling code, where digital prototyping has become a valuable tool. The method comprises kinematically-driven constraints for reaching the target points and for satisfying the joint ranges of motion. The algorithm is driven by a cost function (also called objective function) that is kinetic in nature to minimize approximate energy consumption and visual discomfort.
Technical Paper

Towards Understanding the Workspace of the Upper Extremities

2001-06-26
2001-01-2095
Significant attention in recent years has been given towards obtaining a better understanding of human joint ranges, measurement, and functionality, especially in conjunction with commands issued by the central nervous system. Studies of those commands often include computer algorithms to describe path trajectories. These are typically in “open-form” with specific descriptions of motions, but not “closed form” mathematical solutions of the full range of possibilities. This paper proposes a rigorous “closed form” kinematic formulation to model human limbs, understand their workspace (also called the reach envelope), and delineate barriers therein where a path becomes difficult or impossible owing to physical constraints. The novel ability to visualize barriers in the workspace emphasizes the power of these closed form equations.
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