Research On Gait Planning And Control System Of Hexapod Biomimetic Robot

With the increasingly rapid step of human exploration of the nature, the demand for robots with autonomous mobility under complex environment is getting broader and deeper in many application areas. Legged robot, as a replacement of wheel or track mobile mechanism, has received more and more attentions for its superiority on traversing unstructured terrain.Hexapod robots which have redundant legs are adaptive to the terrain and able to keeping working in the case of losing some legs. Therefore, they are suit for tasks with strict demands on independency and reliability, such as spying in the wild, searching underwater and exploring the outer space. However, the characteristic of multi-legged increases the complexity of their control system at the same time. As the most successful moving creature on the earth, multi-legged insects can facilely manage to surmount various complex natural landforms and even walk upside down on smooth surfaces by right of their sophisticated limb structure and dexterous locomotion control strategies. Accordingly, it has great theoretical and practical significance to take behavioral research effect of multi-legged insect into consideration for the design and control of walking robot and the development of hexapod biomimetic robots with more superexcellent mobility.In this work, a thorough investigation of configuration design, kinematics analysis, gait planning and contriving of control system is made based on bionics, moreover, simulation is performed and the results show that the presented CPG controller can generate different gaits and change its rhythmic patterns smoothly.Firstly, the development, current applications and research status of hexapod robot are reviewed. And the purpose and task of this study are also introduced.Secondly, the design of hexapod robot and its gait principle are illustrated. The gaits of typical straight line movement and specific point swerve are designed and analyzed. The gait generating method for hexapod robot based on rhythm neural network is put forward.Thirdly, according to the control requirements on motion harmony and accuracy of the hexapod bionic robot, a Central Pattern Generator (CPG) controller based on the Hopf and Wilson-Cowan neural oscillator which is known as a weakly neural network that generates fundamental rhythmic movements in locomotion of animals is proposed for robot rhythmic locomotion control. The theory of gait shows the proposed CPG is easy to implement, has fewer parameters, and is able to generate rapid, successive, and steady movement. The selection of parameters used in the CPG is also studied using computer numerical simulation, during which the output changes respect to the parameters and the feasible parameter range are recorded. Moreover, parameters optimization method commonly used in the applications are also surveyed.Finally, based on the CPG controller and selected parameters, the control of the typical hexapod gait is realized. Different rhythmic locomotion models and switching between the models are achieved by replacing the gait matrix of neural oscillators. The parameter normalization is introduced to control the output amplitude of the CPG easily.The Matlab simulation results show that the presented CPG controller can generate different gaits and change its rhythmic patterns smoothly, and the gait planning method is effective. The work of this thesis lays a good foundation for further studies on the hexapod robots.