Research on motion control method of six-degree-of-freedom mechanical arm based on multiobjective optimization

In order to improve the efficiency and accuracy of the mechanical arm in multi-task execution, for the mechanical arm motion path optimization problem, this paper proposes a motion control method based on multi-objective optimization. Firstly, the six-degree-of-freedom mechanical arm is modeled to analyze the influence of its joint angle path on the end-effector accuracy, energy consumption and path planning, and a multilevel optimization strategy to minimize the end-effector error and energy consumption is proposed. The article designs a joint angle path optimization algorithm based on minimizing the effector positioning error by establishing the kinematics and dynamics model of the mechanical arm and under the condition that the initial parameters are known. Secondly, an optimization model combining the joint rotational inertia and average angular velocity is proposed to achieve the dual optimization of effector positioning error and energy consumption under the consideration of mass and end load. In addition, in order to cope with obstacles and complex working environments, a base path planning based on raster graph is designed and combined with joint angle path optimization to achieve the task of bypassing obstacles and returning to the starting point. Finally, this paper utilizes genetic algorithm to solve the proposed model to verify that the mechanical arm can still complete the task efficiently and accurately under the complex environment.