Research On Motion Planning And Trajectory Tracking Control Of Citrus Picking Robot Manipulators

Citrus is essential to our agriculture because it is the fruit grown in most planted areas in the country.Currently,the citrus harvest is mainly manual,which makes the harvest cost high and the harvest efficiency low.In citrus harvesting,it is hard to meet the market’s demands for automation and intelligence.Therefore,the research and development of citruspicking robots are significant for liberating productivity and improving production efficiency.The robot manipulator is the main body of the citrus-picking operation.There are some mature algorithms in the theory of its control problem.Still,most of the work is limited to theoretical discussions and numerical simulations of the control algorithm under the exact model.When there are a lot of unknowns in the model,like unknown dynamic parameters and input saturation constraints,picking citrus will be less accurate and less efficient.To make the picking robot manipulator operate more smoothly and increase the citrus picking robot’s trajectory tracking accuracy,this paper uses the six-degree-of-freedom robot manipulator EC63 as the research object to study the trajectory planning and trajectory tracking control of the citrus picking robot manipulator.The main contents are as follows:(1)The EC63 6-DOF robot manipulator was taken as the research object for kinematic analysis.First,the math base behind kinematics analysis is explained,including how to describe the position and change the coordinates.Second,the coordinate axis of the robot manipulator is set,the DH parameter method is used to get the parameter table of its connecting rod,and the forward kinematic equation of the manipulator is obtained.Then the analytical method was applied to find the inverse operation to get the analytical solutions of the six joints.A robot manipulator model was made in MATLAB,and its forward and inverse kinematic solutions were checked.The results showed that the manipulator’s forward and inverse kinematic solutions matched the actual robot manipulator.(2)The EC63 6-DOF robot manipulator was used as the research object for planning trajectories in joint space and cartesian space.The cubic and quintic polynomial interpolation algorithms are derived in joint space.In cartesian space,trajectory planning is divided into linear and circular interpolation to pursue research.Experiments in simulation and real manipulators verify the feasibility of the algorithm.(3)The EC63 6-DOF robot manipulator was used as a research object to make the algorithm for controlling trajectory tracking.First,the Lagrange method was used to model the dynamics of the robot manipulator.The established dynamics model was used as the focus of the research,and the complexity of the dynamic parameters of the 6-DOF robot manipulator and the effect of disturbances from the outside were considered.Secondly,by importing the URDF model to Simulink,the process of establishing complex dynamic parameters is avoided,which makes the control design of the 6-DOF robot manipulator more efficient.Then the fuzzy logic system is used to approximate the unknown dynamic parameters in the system,and the adaptive law is updated to obtain the estimated values of the unknown parameters.Finally,a modeless adaptive fuzzy dynamic surface controller is designed.Lyapunov stability analysis proves that all the states and signals of the designed closed-loop system with a modeless controller are bound.Finally,comparative experiments demonstrate the proposed control scheme’s effectiveness.(4)Using the EC63 6-DOF robot manipulator as the research object,an adaptive fuzzy backstepping controller is proposed to solve the input saturation constraint problem.Firstly,the basic concepts of input saturation constraint,research status,and backstepping method are introduced to prepare for controller design in advance.Secondly,a dynamic model of a 6-DOF robot manipulator with an input saturation constraint was established,and the input saturation function was transformed.In addition,fuzzy logic systems are used to approximate unknown dynamic parameters and virtual controller terms.Then,a simple design method is used to deal with the nonlinear input saturation problem.The norm of the weight matrix and the upper bound of unknown parameters are estimated using the adaptive law.Combining the estimated value and the backstepping control method,a simple structured adaptive fuzzy backstepping control scheme without an accurate model is proposed.Lyapunov stability analysis proves the proposed control scheme can ensure consistent final bounding trajectory tracking errors.Finally,comparative simulation verifies the proposed control method’s effectiveness.