Research On Autonomous Navigation And Attitude Control System Of Hexapod Robot In Unknown Environment

Hexapod robot has the advantages of good stability,flexible gait and strong load capacity,making it widely used in many fields.In the research of the hexapod robot,the function of autonomous navigation and the attitude control of the body are the focus and difficulty of the research.In this paper,hexapod robot is used as the research object,and the navigation performance and the attitude control performance of the hexapod robot under the unknown environment are studied.Firstly,the hexapod robot control system is designed,which includes the central control layer,the steering gear drive layer,the power supply layer,the environmental information sensing layer and the algorithm layer.Secondly,aiming at the autonomous navigation problem of hexapod robot in unknown environment,a neural network algorithm based on environmental information classification is proposed in this paper.Aiming at the problem that the hexapod robot in the rough road can be tilted,this paper proposes a hexapod robot instability adjustment algorithm based on ZMP(zero moment point).And the two algorithms are programmed to build in the hexapod robot control system.Finally,this paper verifies the validity and reliability of the proposed two algorithms through experiments.The research contents of the hexapod robot are mainly divided into the following aspects:1.The hexapod robot control system based on ARM chip stm32 is designed,which mainly includes a central control layer,a steering engine drive layer,a power supply layer,an environment information sensing layer and an algorithm layer.The device selection,circuit design and function realization of each module are introduced in detail.2.This paper studies the neural network navigation control algorithm and control system of hexapod robot based on environmental information classification.The environmental information is obtained by the airborne nine-axis sensor and the GPS sensor as the input of the algorithm,and different neural network algorithm structures are adopted according to different environmental information,which can save the calculation amount of the algorithm and improve the operation speed of the hexapod robot autonomous navigation control system.The output of the algorithm is the forward speed and the forward angle of the hexapod robot,guiding the hexapod robot's autonomous navigation control system to move.In the autonomous navigation and control system of hexapod robot,three-legged forward gait,three-legged turning gait and five-legged walking gait are designed to meet the requirements of hexapod robot during the walking process.3.The ZMP-based hexapod robot instability determination and adjustment control algorithm is designed,and the hexapod robot instability adjustment control system is designed according to the algorithm.Firstly,based on the data of the airborne nine-axis sensor and the foot-end pressure sensor,the double-threshold method instability determination algorithm is constructed to judge whether the hexapod robot is unstable.Secondly,after determining the instability,according to the geometric relationship between the roll angle and the pitch angle,the projected polygon of the fuselage plane on the horizontal plane is obtained.The ZMP stability margin is built by the data returned by the foot pressure sensor,and the instability adjustment is performed to restore the airframe to a stable state.4.The experiments on the control system of hexapod robot show that the navigation control algorithm based on environmental information classification and the instability adjustment algorithm based on ZMP are practical and effective.