| Legged robots have better environmental adaptability than wheeled and tracked robots,allowing for stable movement in rough terrain.Among them,the hexapod robot has superior stability,strong load capacity,flexible motion mode and certain expansibility.However,the redundant degree of freedom and underdrive of hexapod robots pose a challenge to motion planning and control.Facing different external environments,the multi-gait control strategy of hexapod robots is an urgent problem to be solved.Current research on hexapod robots has not fully utilized the redundancy of the limbs to achieve the functional reuse of the legs and arms during limb movement,and the research on the reusable grasping operation capability of the limbs has an extremely strong application value.In addition,the leg-driven wheeled sliding motion of hexapod robot is studied to improve the energy utilization rate of robot movement in flat terrain and realize the long endurance and high efficiency mobile operation of the robot..Therefore,this paper mainly focuses on the stable motion and leg-arm multiplexing grasping operation of a laboratory-developed electric hexapod robot.The main contents are as follows:1.The kinematics and dynamics models of hexapod robots are established.Firstly,the structure of the hexapod robot is introduced,and the forward and inverse kinematics model and Jacobian matrix of the robot are established by using DH parameter method.Then,the limb is equated to the linkage whose mass is concentrated at the center of mass,and the limb dynamics is established by Lagrange dynamics equation.Finally,to simplify the modeling process,a kinematic tree is used to describe the hexapod robot,and a Newton-Euler iterative method based on spatial 6-dimensional coordinates is used to establish the inverse dynamics model of the hexapod robot,which lays the model foundation for the subsequent control algorithm.2.A leg-driven wheel type sliding motion controller is designed.Firstly,the sliding kinematics model of the hexapod robot is established,and the relationship between the pulley speed and the robot posture is analyzed.Then,according to the mapping relationship between plantar force and pulley speed,the leg plantar force and wheeled gliding mapping model is established.Finally,according to the requirement of plantar force on sliding speed,limb motion trajectory was planned by cubic spline function interpolation,and a leg drive sliding motion controller is designed,and on the physical prototype,the straight-line and rotation sliding experiments are conducted to verify the effectiveness of the leg-driven wheel gliding algorithm.3.The multi-step walking motion of a hexapod robot is studied by integrating model predictive control and whole-body motion control methods.Firstly,gait phase of the hexapod robot is divided based on time series,and gait of the hexapod robot is planned,Secondly,the multi-gait control algorithm of hexapod robot is studied.The hexapod robot is equivalent to a single rigid body,and the centroid dynamics model is established.Based on the dynamics model and gait phase,the model predictive control equation is constructed and converted into quadratic programming equation.Then,based on the dynamics model of the hexapod robot,the relaxation optimization equation was constructed by integrating the model predictive control and the whole body control methods,and the optimization equation is transformed into a quadratic optimization problem to obtain the optimal joint control quantity.Finally,the optimized joint control quantity is sent to the hybrid feedforward joint PD controller to solve the joint torque and control the limb motion,realizing the multi-gait walking motion of the robot.The multi-gait omnidirectional walking motion experiment is carried out on the prototype,and the effectiveness of the control method is verified.4.A redundant control method of legs,arms and limbs is studied to improve the operational capability of hexapod robots.Firstly,the working space of limbs is analyzed to provide boundary constraints for grasping trajectory planning.Secondly,based on the static stability margin,the grasping phase and trajectory were planned,and the inverse kinematics model is used to solve the joint Angle,and the front and rear limbs are controlled to plan the trajectory and grasp the object.Then,based on the requirements of limb configuration grasping function in redundant degrees of freedom,the functional reuse of legs and arms is realized by redundant degrees of freedom mode transformation of middle limbs.Based on the Jacobi joint space mapping and impedance terminal trajectory planning controller,the four-legged whole body movements of front and rear limbs are integrated to realize the two-arm mobile grasping.Finally,the effectiveness of the grab motion trajectory planning controller is verified by experiments. |
