Large component collaborative machining planning method for multi-robot collision avoidance coupling planning problem

Abstract

The invention discloses a large component collaborative machining planning method for a multi-robot collision avoidance coupling planning problem. The method comprises: conducting machining area division on multiple robots; judging the processing load balance of the robot, and optimizing the load balance of each processing partition by adopting a task redistribution process; identifying areas, interfering with other subareas, in all robot subareas, and establishing undirected graph models of all interference areas; generating an interference region priority sequence between any two robots, converting the undirected graph model into a directed acyclic graph (DAG) model, and forming an incomplete scheduling plan of multiple robots; embedding non-interference area tasks into incomplete scheduling represented by the DAG; searching a feasible DAG instance, embedding a non-interference area task, judging the collaborative processing efficiency of the current instance, and accepting a better solution until the expected scheduling optimization target is achieved. An effective method for improving the multi-robot cooperation efficiency and safety is provided for large part machining, and practicability and universality are good.

Description

technical field [0001] The invention belongs to the technical field of robot collaborative control, and in particular relates to a large-part collaborative processing planning method for multi-robot collision avoidance coupling planning problems. Background technique [0002] In the manufacturing field typically represented by aerospace, the processing and assembly efficiency of large components directly affects the overall production delivery speed and manufacturing cost of the product. Such parts have the characteristics of large size and complex shape and structure. Traditional machine tools often have the disadvantages of poor accessibility, low flexibility and high cost. [0003] In contrast, robotic processing equipment for the manufacture of such large components has good expected benefits, and a multi-robot collaborative processing system can effectively deal with a large number of repetitive processing and assembly processes. For example, the paper "Machining of la...

AI Technical Summary

Problems solved by technology

However, multi-robot collaborative processing has the problem of optimizing robot safety and processing efficiency: when working around large parts, the work envelopes of each robot overlap and the end effector is large, so it is necessary to fully coordinate the processing process of each robot to avoid collisions and reduce stalls

However, current related methods do not address problems where XD constraints exist

The ILS algorithm usually needs a fast and effective local optimization strategy to ensure the search effect of the solution space, but for the multi-robot collaborative processing problem, efficient local optimization is very difficult due to its XD constraints, which affects the application of the ILS algorithm

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