A q-learning-based trajectory planning method for concrete placing robot

Abstract

The invention relates to a novel trajectory planning scheme of an intelligent concrete placing robot, which is suitable for autonomous pouring control of a concrete placing robot, avoids complex kinematic inverse solution interpolation calculation, and belongs to the field of intelligent manufacturing. The invention designs a general trajectory planning framework, including the rapid movement process of the placing robot from the initial state to the starting point of the path, and the reset from the ending point of the path to the initial state; . In the process of fast motion, a simple interior point method is used to optimize the inverse solution aiming at time optimization, and a cubic polynomial is used to fit the trajectory. In the process of continuous concrete pouring, the path to be poured at the end of the placing robot is formed into an error band of a certain area. The Q-learning algorithm is used to divide the formed path error band into regions, and the divided regions are divided according to the pouring goals and constraints. Given the reward value, the Q-value training is performed on the given grid, and finally the action sequence of each joint of the robot is formed, and the robot action is directly obtained, which avoids the complex trajectory planning process based on kinematic inverse solution optimization.

Description

technical field [0001] The invention relates to a novel trajectory planning method of an intelligent concrete distributing robot, which is suitable for the autonomous pouring control of the concrete distributing robot, avoids complex interpolation calculations, and belongs to the field of intelligent construction. Background technique [0002] The concrete distributing robot is a kind of construction industrial robot that transports concrete to the construction site, and plays a very important role in the development of urban modern construction. With the continuous improvement of the efficiency requirements of the cloth robot in engineering construction, the research on the intelligent control of the cloth robot has gradually developed. Intelligent control is inseparable from the path and trajectory planning of the manipulator. For industrial robots, path planning mainly refers to the trajectory of the movement of the end of the manipulator, and trajectory planning is expre...

AI Technical Summary

Problems solved by technology

At present, for large-scale cloth boom systems, the construction conditions are relatively harsh, and the traditional trajectory planning method has a large amount of calculations, and it is difficult to determine the optimal performance index. , the pouring path of the working section is often planned and judged according to the limited perspective of the on-site staff, and the quality of the construction pouring is overly dependent on the worker's operating experience and technical level, and the degree of automation is low, which cannot meet the trajectory movement requirements of the pouring end of the large-scale distribution boom system

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