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Initial spatial motion of a rigid body on removal of one constraintBatra, Ajoy 19 October 1993 (has links)
This thesis presents a discussion of motion of a six-legged walking
machine following removal of one leg constraint. To take a step, one leg
must be lifted and placed at some other position. As soon as the constraint
provided by the leg is removed, however the machine begins to fall. This
falling motion can be represented as screw motion of the body center of
mass and of body-leg attachments.
First a study of body workspace of the machine was done with all six
feet on the ground. Body workspace is the intersection of kinematic and
force workspaces. Kinematic workspace is the volume in space where the
center of mass can be placed such that all joint angles of legs are within
specified limits; and force workspace is the volume in space where the force
in all legs is compressive. The affect of various foot positions, pitches and
heights of the center of mass were investigated to find a set of three
symmetric foot positions that might constitute acceptable intermediate
positions in a walking sequence.
Motion of the center of mass in the forward direction is limited in the
force workspace by two points at which the force on a pair of legs goes to
zero. With the center of mass at each of these two positions, the screw
parameters resulting from the release of force on one leg (front, middle and
hind individually) could be determined.
Dynamic simulation of these body and foot positions used the
commercial software SD/FAST. Code was written in C to do both static and
dynamic simulation of machine and merged with code generated by
SD/FAST. Code was also written in Auto Lisp to plot the falling motion of
machine.
Screw parameters found in this study were such that sustained
forward motion of the body could not be achieved using the falling motion
alone. Other measures such as extending one or more of the remaining five
legs would be needed for effective forward body motion. / Graduation date: 1994
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Human expression and intention via motion analysis: learning, recognition and system implementation. / CUHK electronic theses & dissertations collection / Digital dissertation consortiumJanuary 2004 (has links)
by Ka Keung Caramon Lee. / "March 29, 2004." / Thesis (Ph.D.)--Chinese University of Hong Kong, 2004. / Includes bibliographical references (p. 188-210). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. Ann Arbor, MI : ProQuest Information and Learning Company, [200-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Mode of access: World Wide Web. / Abstracts in English and Chinese.
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Capture of human motion from image sequence using genetic algorithm. / 遺傳演算法的應用連續影像之人體動作捕捉 / Capture of human motion from image sequence using genetic algorithm. / Yi zhuan yan suan fa de ying yong lian xu ying xiang zhi ren ti dong zuo bu zhuoJanuary 2003 (has links)
Wai Yin Yee = 遺傳演算法的應用連續影像之人體動作捕捉 / 韋燕儀. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2003. / Includes bibliographical references (leaves 113-115). / Text in English; abstracts in English and Chinese. / Wai Yin Yee = Yi zhuan yan suan fa de ying yong lian xu ying xiang zhi ren ti dong zuo bu zhuo / Wei Yanyi. / Abstract --- p.ii / 摘要 --- p.iv / Acknowledgement --- p.vi / Content --- p.vii / List of Figures --- p.x / List of Tables --- p.xviii / Chapter Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Human Motion Capture --- p.1 / Chapter 1.1.1 --- Optical Motion Capture --- p.3 / Chapter 1.1.2 --- Monocular Motion Capture --- p.4 / Chapter 1.2 --- Proposed Human Motion Capture System --- p.6 / Chapter 1.3 --- Organization --- p.8 / Chapter Chapter 2 --- Introduction of Genetic Algorithms --- p.10 / Chapter 2.1 --- Traditional Search Methods & Genetic Algorithms --- p.11 / Chapter 2.2 --- Mechanism of Genetic Algorithms --- p.14 / Chapter 2.3 --- A Simple Genetic Algorithm --- p.16 / Chapter 2.3.1 --- Initialization --- p.16 / Chapter 2.3.2 --- Evaluation --- p.17 / Chapter 2.3.3 --- Selection --- p.18 / Chapter 2.3.4 --- Genetic Operation --- p.19 / Chapter 2.3.5 --- Termination --- p.23 / Chapter 2.4 --- Convergence Proof for GA --- p.24 / Chapter 2.5 --- Proposed Modified Genetic Algorithm --- p.26 / Chapter 2.6 --- Effectiveness of the Proposed Modified GA on Function Optimization --- p.28 / Chapter 2.6.1 --- Function 1 - Unimodal function --- p.28 / Chapter 2.6.2 --- Function 2 - Sine function --- p.35 / Chapter 2.6.3 --- Function 3 - Foxhole function --- p.39 / Chapter 2.6.4 --- Function 4 - Discrete function --- p.41 / Chapter Chapter 3 --- Pre-processing I - Articulated Stick Model --- p.44 / Chapter 3.1 --- Background Knowledge of Human Skeleton --- p.44 / Chapter 3.2 --- Simplified Humanoid Articulated Stick Model --- p.44 / Chapter Chapter 4 --- Pre-Processing II - Reference Lengths & 2-D Frame Scale --- p.48 / Chapter 4.1 --- Optimization Approach --- p.54 / Chapter 4.1.1 --- Parameters Range --- p.62 / Chapter 4.1.2 --- GA Formulation --- p.63 / Chapter 4.2 --- Triangulation approach --- p.63 / Chapter 4.3 --- Experiments & Discussion --- p.66 / Chapter 4.3.1 --- Experiment One: Synthetic sequences --- p.67 / Chapter 4.3.2 --- Experiment Two: Real image sequences --- p.71 / Chapter Chapter 5 --- Pre-Processing III - Possible Depths --- p.76 / Chapter Chapter 6 --- Resolving Depth Ambiguity by GA --- p.83 / Chapter 6.1 --- Smoothness Assumption --- p.83 / Chapter 6.2 --- Kinematic Constraint --- p.85 / Chapter 6.3 --- GA Formulation --- p.85 / Chapter 6.4 --- Proposed Constrained GA --- p.86 / Chapter 6.5 --- Implementation and Experiments --- p.87 / Chapter 6.5.1 --- Experiment One: Synthetic sequences --- p.88 / Chapter 6.5.2 --- Experiment Two: Real image sequences --- p.105 / Chapter Chapter 7 --- Conclusion --- p.111 / Bibliography --- p.113 / Appendix A Description of Rotating Angles --- p.116
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