Modular Control Unit And Force Control Study Of Hexapod Robot

Because the design idea of hexapod robot was from the arthropods, so that it had a strong ability to adapt complex terrain. In addition, that lower organisms can adapt complex unstructured terrain give us important inspiration. Reflex control unit of leg system based on perception and the nervous system can simplify complex motion. Therefore, this issue was from the point of functional bionic and control bionic. The core idea was modular leg and the underlying motion planning. By leg system and force control unit was designed to subsystem, hexapod robot can achieve efficient and stable walking motion.First of all, the modular leg system with independent control unit and sensing system was designed. This paper used ARM processor as the core control unit, EPOS2 Module 36/2 module as a driver driveing three motors of the leg and CANopen to accomplish communication between servo motor driver and the leg controller. On the basis of the original sensor configuratio n of leg system, the force signal acquisition module of the foot end was designed. And this paper designed a filter circuit and use an active second-order low-pass filter for filtering the signal of strength.Secondly, before designing control algorithms, its kinematics was analyzed. So this paper analyzed forward kinematics, inverse kinematics and Jacobian matrix. According kinematic equations the foot end’s workspace of the swing leg was analyzed, the results showed that the robot had a good exercise flex ibility. And under three-legged support, the relationship between the pose’s torso and the supporting leg’s joints angle was analyzed.Thirdly, the compliance control strategy of the force at the foot end was used to improve the stability of rough terrain robot. This paper designed the force tracking control algorithms based on impedance control theory. According to the environmental model, the relationship between steady force error and environmental parameters was analyzed. To improve the original algorit hm, the environmental parameters online identification algorithm was applied in force tracking algorithm. Finally the model reference adaptive method was used to compensate the uncertainty of the environmental model, so that the author can improve the applicability of force tracking algorithm. Environmental parameters online identification algorithm and model reference adaptive methods were designed based on the Lyapunov stability theorem.Finally, in order to verify the correctness of algorithm analysis pr ocess, this paper simulated the force tracking algorithm using Simulink and Adams. After the simulation was completed, the physical experiment was performed. The results showed that the underlying leg system unit developed by this paper was effective, and in the environment with unknown parameters the proposed force control algorithm can effectively improve the stability of the robot’s movement.