Research On Controller-in-the-loop Simulation Of Heavy Intelligent Salvage Robot

The intelligent salvage operation intends to use ship-borne robots to grasp and reliably recover high-value floating objects on the sea surface under high sea conditions.In order to solve a series of core technical problems involved in wave dynamics analysis,functional design of large-scale tandem robots,prediction of floating objects on the sea surface,and intelligent capture of floating objects on the sea surface,a semi-physical simulation system needs to be constructed and mature simulation technology Optimize the design and train the control algorithm.Considering the complexity of controller algorithm design and verification,it is particularly necessary to construct a controller-in-the-loop simulation system for design.Based on the existing hardware-in-the-loop simulation system,this paper designs the controller-in-the-loop simulation system.In order to match the signal connection in different simulation modes,the system information flow is designed.Integrate the models of hydraulic system and mechanical syst em into a real-time simulation platform.The kinematics model and trajectory planning are integrated in the upper computer,the control algorithm is integrated in the lower computer,and the communication method between the upper and lower computers is for mulated.According to the analysis of robot kinematics and dynamics,the forward kinematics model of the robot is established,and the inverse kinematics of the robot is solved by the analytical method,BP neural network method,and Newton method.The effects of these three methods are compared.Then,the robot dynamics model and the manipulator dynamics model were established respectively,which provided a simulation model for the controller-in-the-loop simulation.The trajectory of the robot is planned.First,the relative position in the tracking process is designed so that when the robot tracks the target,it can ensure that the target is within the observation range of the vision camera.Then the trajectory planning was carried out in the joint space,and the 4-3-4 trajectory and the acceleration trajectory were used for planning,and the two methods were compared.The results show that the trajectory based on the acceleration trajectory planning method is smoother and can reduce the impact.At the same time,an anti-collision mechanism is designed for the collision phenomenon that may occur in the experiment.The simulation results show that the anti-collision mechanism can effectively avoid the collision and ensure the safety of the experiment.To design the robot control system,firstly model the robot hydraulic drive system.Considering that during the capture process,the manipulator may collide with the target to a greater extent,in order to ensure the compliance of the capture process and avoid equipment damage,a compliance control algorithm is designed for the robot.At the same time,considering the impact of structural mutation after the robot captures the target,a variable load control algorithm is designed.The simulation results show that the designed control algorithm can successfully track and capture the target by the robot.Finally,the controller-in-the-loop simulation system is used for overall debugging and experimental verification,the controller hardware is connected to the simulation object,and the controller is simulated by the object,which verifies the effectiveness of the target capture strategy.