5 research outputs found
Legged robot gait locus generation based on genetic algorithms
Achieving an effective gait locus for legged robots is a challenging task. It is often done manually in a laborious way due to the lack of research in automatic gait locus planning. Bearing this problem in mind, this article presents a gait locus planning method using inverse kinematics while incorporating genetic algorithms. Using quadruped robots as a platform for evaluation, this method is shown to generate a good gait locus for legged robots. Copyright © held by author
Microsoft robotics soccer challenge : movement optimization of a quadruped robot
Estágio realizado na Universidade de Aveiro e orientado pelo Prof. Doutor Nuno LauTese de mestrado integrado. Engenharia Electrotécnica e de Computadores. Faculdade de Engenharia. Universidade do Porto. 200
Using Fourier Analysis To Generate Believable Gait Patterns For Virtual Quadrupeds
Achieving a believable gait pattern for a virtual quadrupedal character requires a significant time investment from an animator. This thesis presents a prototype system for creating a foundational layer of natural-looking animation to serve as a starting point for an animator. Starting with video of an actual horse walking, joints are animated over the footage to create a rotoscoped animation. This animation represents the animal’s natural motion. Joint angle values for the legs are sampled per frame of the animation and conditioned for Fourier analysis. The Fast Fourier Transform provides frequency information that is used to create mathematical descriptions of each joint’s movement. A model representing the horse’s overall gait pattern is created once each of the leg joints has been analyzed and defined. Lastly, a new rig for a virtual quadruped is created and its leg joints are animated using the gait pattern model derived through the analysis
Reliable and precise gait modeling for a quadruped robot
Abstract. We present a parametric walk model for a four-legged robot. The walk model is improved using a genetic algorithm, but unlike previous approaches, the fitness is determined in a run that closely resembles the later application. We thus not only achieve high speeds, but also a high degree of flexibility. In addition to the walking model being flexible, we present a means of automatically calibrating the walking engine. This allows for highly precise robot control and greatly improved odometry accuracy. Lastly, we show how the motion model can be extended to integrate specialized motions to further increase locomotion speed without compromising flexibility.