A trajectory generation method for balancing impact dynamic loads in robot pick-and-place tasks

Abstract

The invention discloses a trajectory generation method for balancing impact dynamic loads in a robot pick-and-place task, which obtains connecting rod and joint parameters, obtains a pose mathematical model of a six-axis robot joint and an end effector, and obtains three intersecting connecting rods The position of the intersection point, and the axis angles of the three connecting rods that are set to intersect are obtained by calculating the end-rotary rod components, and the sum of the products of the externally applied force and the virtual displacement set of the generalized coordinates is zero to obtain the Lagrangian Model, slide to select multiple path points for trajectory fitting, get the pick-and-place motion trajectory, obtain the set power value to optimize the external load distribution torque, calculate the joint rotation angle according to the set optimized power value, and combine the obtained The pick-and-place motion trajectory is described, and the optimized pick-up trajectory is obtained, which improves the control accuracy of the robot in the process of completing the pick-and-place task, and ensures that the pick-and-place position is accurate.

Description

technical field [0001] The invention relates to the technical field of robot grasping, in particular to a trajectory generation method for balancing impact dynamic loads in robot pick-and-place tasks. Background technique [0002] In industrial occasions, robots are usually used to grab products and move from one position to the next. The robot completes the pick-and-place task under dynamic load impact conditions. Since the product itself has its own weight, the robot controller needs to be able to distribute the external load reasonably through the distribution optimization of the dynamic load of the mechanism, so as to achieve smooth movement. At present, the visual sorting task in the industrial environment is usually driven by the controller and the end hand. The claw completes the grabbing action. Take the grabbing of boxed products as an example. First, the controller drives the robot to grab the boxed product, and then lowers the gripper of the robot to the grabbing ...

AI Technical Summary

Problems solved by technology

Since the product itself has its own weight, the robot controller needs to be able to distribute the external load reasonably through the distribution optimization of the dynamic load of the mechanism, so as to achieve smooth movement. At present, the visual sorting task in the industrial environment is usually driven by the controller and the end hand. The claw completes the grabbing action. Take the grabbing of boxed products as an example. First, the controller drives the robot to grab the boxed product, and then lowers the gripper of the robot to the grabbing point through pose calculation, and then drives the robot to grab , move and complete the task of stacking, but due to the influence of the gravity of the object itself, there will be a certain load impact on the control model of the industrial robot, which will lead to the low control accuracy of the robot during the process of completing the picking and placing task, and the picking and placing position will not be correct. precise

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