Abstract
Palletizing robot is widely used in logistics operation. At present, people pay attention to not only the loading capacity and working efficiency of palletizing robots, but also the energy consumption in their working process. This paper takes MD1200-YJ palletizing robot as the research object and studies the problem of low energy consumption optimization of joint driving system from the perspective of trajectory optimization. Firstly, a multifactor dynamic model of palletizing robot is established based on the conventional inverse rigid body dynamic model of the robot, the Stribeck friction model and the spring balance torque model. And then based on joint torque, friction torque, motion parameter, and joule’s law, the useful work model, thermal loss model of joint motor, friction energy consumption model of joint system, and total energy consumption model of palletizing robot are established, and through simulation and experiment, the correctness of the multifactor dynamic model and energy consumption model is verified. Secondly, based on the Fourier series approximation method to construct the joint trajectory expression, the minimum total energy consumption as the optimization objective, with coefficients of Fourier series as optimization variables, the motion parameters of initial and final position, and running time constant as constraint conditions, the genetic algorithm is used to solve the optimization problem. Finally, through the simulation analysis the optimized Fourier series motion law and the 3-4-5 polynomial motion law are comprehensively evaluated to verify the effectiveness of the optimization method. Moreover, it provides the theoretical basis for the follow-up research and points out the direction of improvement.
Highlights
Palletizing robots have been widely applied in logistics operations such as storage, handling, and transportation of materials
This paper takes MD1200-YJ high speed and heavy load palletizing robot developed by Tianjin University in China as the research object and researches the minimum energy consumption of joint drive system which is the core of driving the manipulator to complete the motion control, and it is the main link of energy consumption, from the perspective of trajectory planning
Pellegrinelli S et al [25] researched the analysis and optimization of the energy consumption related to auxiliary robotic assembly processes, a frictional model considering the coulomb-viscous friction and inverse dynamic model were established, and an energy consumption model including constant power mechanical power and copper loss of motor was established, a method for automatic generation of collision-free trajectories was proposed to reduce the energy of the work cycle by 12%
Summary
Palletizing robots have been widely applied in logistics operations such as storage, handling, and transportation of materials. Paes K et al [4] to ABB’s IRB1600 industrial robot as the research object and proposes a scene recognition and time and energy optimal trajectory planning method, to work space, joint speed acceleration and dynamic parameters as constraint conditions, the minimum cost function based on the energy as the optimization goal. Pellegrinelli S et al [25] researched the analysis and optimization of the energy consumption related to auxiliary robotic assembly processes, a frictional model considering the coulomb-viscous friction and inverse dynamic model were established, and an energy consumption model including constant power mechanical power and copper loss of motor was established, a method for automatic generation of collision-free trajectories was proposed to reduce the energy of the work cycle by 12%. The effectiveness of the optimization method is verified by simulation analysis
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