Energy consumption path planning of food robot based on improved whale algorithm and neural network

Abstract

Objective: In order to solve the energy-saving trajectory planning problem of robot in food industry with unknown dynamic parameters, a point-to-point robot joint energy consumption path planning scheme based on whale algorithm and neural network was proposed. Methods: The energy consumption model of point-to-point joint of mobile manipulator of food robot was constructed, the similarity dynamics identification based on neural network was designed, and the improved whale algorithm was used to optimize the weight and bias parameters off-line. The quadric polynomial interpolation method was used to plan the joint motion trajectory, and the trajectory parameters were equivalent to whale coding. By solving the joint energy consumption objective optimization function, the joint motion planning trajectory with optimal energy consumption was finally obtained. Results: The scheme was suitable for the trajectory planning scene with unknown robot dynamic parameters, and the trajectory energy consumption was reduced by about 9.01%. Conclusion: The trajectory planning based on whale algorithm and neural network can realize the energy consumption optimization goal of food robot.

Keywords

• food robot
• trajectory optimization
• energy consumption optimization
• whale algorithm
• neural network