| Abstract [eng] |
Robot motion generation is an especially relevant problem in robotics, which is often solved by employing ideas from the Nature. One such example of robotics and Nature working together is central pattern generators – neural circuits found inside animals that are responsible for generating rhythmic, repetitive signals without the interference from a higher level control system. The central pattern generator algorithm was adapted for the motion generation of a hexapod robot in this work. In-depth analysis of the algorithm was performed and alternative forms of its adaptation were proposed for generation of diverse movement characteristics. An improvement over the central pattern generator algorithm was proposed and implemented, which includes a reflexive system that is capable of reacting to the surroundings of the robot, in turn avoiding obstacles and planning its further trajectory. The optimal leg configuration of the robot was also selected in the work, which allows maintaining the optimal ratio between the robot’s stability and movement speed. The theoretical work was applied in a simulated model of the robot, that is capable of navigating through unknown environments and avoiding obstacles. |
