Research on dynamic programming of coal and gangue sorting robot based on greedy strategy

Purpose In the context of coal mine intelligent construction, intelligent sorting of coal gangue based on robot technology has become one of the main development directions for gangue sorting. The sorting sequence and path of gangue depend on the dynamic sorting planning algorithm, which plays a crucial role in determining the efficiency and energy consumption of coal gangue sorting robots. The purpose of this paper is to solve the inefficiency of existing algorithms and propose a dynamic sorting planning algorithm based on greedy strategy for continuous coal gangue sorting by Delta robot. Design/methodology/approach First, the visual recognition system processes images of gangue flow and extracts the position and quality information of each gangue. Considering the variation in coal gangue quality and sorting distance, a robot energy consumption index is introduced. To optimize the greedy algorithm and reduce active omissions in gangue sorting, a correction function is introduced. Divide the gangue flow on the conveyor belt into continuous time window areas in time T, and calculate the sorting order and sorting path of all gangue within the current time window through an optimized greedy algorithm. Finally, MATLAB simulation and robot experiment are carried out to compare the two gangue sorting planning algorithms. Findings Based on the optimized greedy algorithm under the energy consumption index, a better sorting sequence and sorting path are planned in gangue sorting; Under two different gangue flow densities, compared with the sequential planning algorithm, the optimized greedy algorithm can successfully sort more gangue in a shorter time and with lower energy consumption, which verifies that this algorithm can effectively improve the sorting efficiency of gangue. Originality/value In response to the low efficiency, high energy consumption and significant sorting omissions inherent in traditional sequential planning algorithms, a refined greedy strategy planning algorithm has been developed for gangue sorting Delta robots. This refinement has resulted in enhanced robot efficiency, decreased energy consumption and alleviated sorting omissions.