A discussion of the theory and methodology for creating believable quadrupedal locomotion for computer animation applications. The study focuses on a variety of issues related to producing realistic animal gait animations and includes a case study for rigging and animating the various gaits of a horse. Visualization of unnatural gaits for the horse will also be discussed and animated. The process of rigging involves setting up the character control system in a high-end 3d computer animation program such as Maya which is used extensively by the computer graphics industry.

In this thesis, a snake like robot is implemented for search and rescue applications. The snake is intentionally selected as a reference for their ability to move on various environments, but due to the mechanical limitations the implemented snake-like robot design could not be close to the biological counterparts. Although the implemented snake like robot is not a replica of biological snakes / it captured key aspects of snakes such as flexibility, redundancy and high adaptation. To depart from the mechanical limitations / a model of the implemented robot is designed in MATLAB - SIMMECHANICS including a model for the environment. The implemented model is based on the implemented snake like robot but possessed extra features. The model is controlled to perform common snake gaits for navigation. Obstacle avoidance, object (debri or victim) v reaching and object dragging behaviors are acquired for the implemented gaits. Object dragging is accomplished by pushing an object by head or the body of the robot without lifting. For effective navigation, appropriate snake gaits are conducted by the model. All control operations such as obstacle avoidance for each gait and gait selection / a network of self tunable FACL (fuzzy actor critic) fuzzy controllers is used. Although the adapted snake gaits result in the movements which have properties that are not a replica of the real snake gaits, self tunable controllers offered best available combination of gaits for all situations. Finally, truncated version of the controller network, where the implemented mechanical robot&amp / #8217 / s abilities are not breached, is attached to the mechanical robot.

In this thesis work an intelligent controller based on a gait synthesizer for a hexapod robot used in rescue operations is developed. The gait synthesizer draws decisions from insect-inspired gait patterns to the changing needs of the terrain and that of rescue. It is composed of three modules responsible for selecting a new gait, evaluating the current gait, and modifying the recommended gait according to the internal reinforcements of past time steps. A Fuzzy Logic Controller is implemented in selecting the new gaits.

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The aim of this thesis is to determine the horse’s gait types using the acceleration values measured from the horse. A measurement was taken in Gävletravet, a total of five Nanotrak sensors were used, four on the different parts of the horse, and one on the hand of the horse’s driver, a car was driven parallel to the horse and the motions of the horse was recorded by a camera in order to synchronize with the data measured by the sensors, a total of four videos were recorded. The software to process the data was Matlab R2010b, and the methods to analyze them were Fast Fourier Transform (FFT), Short Time Fourier Transform (STFT), and Least Squares (LS). Different window functions were tried when applying the STFT, and the Hanning window was the best to smooth the curves, different window sizes (or data length) were also tried, the data length of 512 was found to be the most proper value. The methods for classification of horse’s gaits included amplitude, ratio, and LS. The method of amplitude worked well for the first three videos except for the last one, and performed better than the other two. The method of ratio was more reliable, but the results were not satisfactory. The method of LS gave bad results, so it was not trustworthy. More measurements and more analysis needed to be done in the future to find a proper way to automatic determine the horse’s gaits, and the use of modern technology will be very popular in other fields like animal science.

xx, 287 p. ; ill. (some col.) A print copy of this title is available through the UO Libraries under the call numbers: SCIENCE QP310.W3 W55 2008 / Digital three-dimensional (3D) models are useful for biomechanical analysis because they can be interactively visualized and manipulated. Synthesizing and analyzing animal locomotion with these models, however, is difficult due to the large number of joints in a fully articulated skeleton, the complexity of the individual joints, and the huge space of possible configurations, or poses, of the skeleton taken as a whole. A joint may be capable of several biological movements, each represented by a degree of freedom (DOF). A quadrupedal model may require up to 100 DOFs to represent the limbs and trunk segments only, resulting in extremely large spaces of possible body configurations. New methods are presented here that allow limbs with any number of biomechanical DOFs to be kinematically exercised and mapped into a visualization space. The spaces corresponding to the ranges of motion of the left and right limbs are automatically intersected and pruned using biological and locomotion constraints. Hind and fore spaces are similarly constrained so that Genetic Algorithms (GAs) can be used to quickly find smooth, and therefore plausible, kinematic quadrupedal locomotion paths through the spaces. Gaits generated for generic dog and reptile models are compared to published gait data to determine the viability of kinematics-only gait generation and analysis; gaits generated for Apatosaurus, Triceratops , and Tyrannosaurus dinosaur models are then compared to those generated for the extant animals. These methods are used for several case studies across the models including: isolating scapulothorax and shoulder joint functionality during locomotion, determining optimal ankle heights for locomotion, and evaluating the effect of limb phase parameters on quadrupedal locomotion. / Adviser: Kent A. Stevens

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Pose estimation uses computer vision to predict how a body moves. The likeliness off different movements is predicted with a neural network and the most likely pose is predicted. With DeepLabCut, an open source software package for 3D animal pose estimation, information about animals behaviour and movement can be extracted. In this report the pose estimation of horses four hooves is used. By looking at the position of the hooves different gaits can be identified. Horses used for riding in the major disciplines in Sweden have three different gaits, walk, trot and canter. Walk is a four-stoke gait, trot is two-stoke and canter is three-stoke. This can be used to classify the different gaits. By looking at the hooves movement in vertical position over time and fitting a sinewave to the data it is possible to see the phase difference in the hooves movement. For walk and trot there was a significant pattern which was easy to identify and corresponded well to the theory of horses movement. For canter our pre-trained model lacked in accuracy, so the output data were insufficient. Therefore it was not possible to find a significant pattern for canter which corresponds to the theory of horses movements. The Fourier Transform were also tested to classify the gaits and when plotted it was possible to detect the different gaits, but not significant enough to be reliable for different horses in different sizes running in different paces. It was also possible to add the data for all four hooves together and fit a sinewave to the added data, and then compare it with the sinewaves for each hoof separately. Depending on the gait the frequency of the sinewaves differed between the hooves separately and added together and the gaits could be identified.