Research On Motion Parameter Optimization Of Industrial Robot For Time And Energy Consumption

Industrial robots are widely used in all walks of life due to their highly automated and intelligent work capabilities.Especially after the concept of Industry 4.0 was put forward,the research and application of industrial robots were accelerated.However,the high energy consumption of industrial robots has gradually attracted people's attention.In order to maximize production efficiency,energy consumption must be minimized while ensuring production efficiency.Aiming at the above problems,this paper takes a six-degree-of-freedom series industrial robot as the research object,and proposes a motion parameter optimization method for industrial robot oriented to time and energy consumption.The main contents are as follows:(1)Based on the analysis of the composition of industrial robot system,the working time of the robot is analyzed from the planned time of the robot,the factors affecting the working time are summarized,and the working time model is established.From the perspective of energy flow,the energy consumption of the robot in the working process is analyzed and modeled.Taking the above two factors into account,a generalized model of time and energy consumption is established.The relationship between them is analyzed theoretically.(2)Aiming at the problem of time and energy consumption of industrial robot,a modeling method based on time and energy consumption is proposed.In order to ensure the smoothness of the robot motion and reduce the computation,the fifth degree polynomial is finally selected to fit the joint motion trajectory of the robot through the comparison of a variety of trajectory functions.The kinematics of the robot is analyzed,and time and energy consumption models are established on the basis of kinematics and dynamics.In order to obtain the robot motion parameters with the optimal time and energy consumption,the concept of green degree was introduced,and the two-objective model was converted into a single-objective model by weight coefficient distribution method,and the final objective function was obtained.(3)Aiming at the problem of solving the objective function,an improved particle swarm optimization algorithm is proposed based on the basic particle swarm optimization(PSO)algorithm.Four common test functions are introduced.Standard particle swarm optimization,PSO algorithm with linear decreasing inertia coefficient and the improved particle swarm optimization algorithm proposed in this paper are used to optimize the four test functions respectively.By comparing the results,the applicability of the improved algorithm is proved.(4)In order to verify the feasibility of the proposed method,the MDF automatic production line developed by the project team is taken as an example to analyze the motion process of the industrial robot in detail.According to the motion parameter optimization model oriented to time and energy consumption,the improved particle swarm is adopted.The algorithm is solved,and the results obtained by comparing the cubic polynomial and the fifth-order polynomial prove that the selected trajectory and method are better,and the optimal robot motion parameters are obtained.By constructing an experimental platform centered on the Fanuc Robot LR Mate 200 i D robot,the same path was run,and the results obtained were similar to those obtained from the case.