基于贪心策略的直角坐标机器人动态分拣规划

针对直角坐标机器人在动态分拣过程中顺序规划算法效率低下的问题，提出了一种适用于机器人连续分拣作业的改进贪心策略规划算法。建立直角坐标机器人的运动学模型，确保物体被准确拾取。设计时间窗口，对传送带上的连续运动物体进行区域划分，并应用贪心策略对同一时间窗口内的物体规划分拣顺序。考虑物体存在分拣遗漏的风险，设计评价函数对贪心策略进行改进，增强了所提算法的实用性。设计模拟程序对所提算法进行仿真，并利用搭建的机器人平台开展分拣实验，验证了算法的可行性和有效性。实验表明:所提算法可在机器人实际分拣作业中规划出有效的分拣路径，平均分拣距离和分拣时间均小于顺序规划算法，提高了机器人对平面随机分布的连续运动物体的分拣效率，实时性好，实用性强，对机器人动态分拣场景下的分拣路径优化研究具有一定的指导意义。 

Dynamic sorting planning of Cartesian robot based on greedy strategy

An improved greedy strategy planning algorithm for continuous robot sorting is proposed for the problem that the efficiency is low when traditional sequential sorting algorithm is applied to sort dynamically materials with Cartesian robot. Kinematic model of the Cartesian robot was established to ensure that materials can be accurately picked up. Time window was designed to divide the continuous flow materials on the conveyor belt into regions one by one, and the greedy strategy was applied to plan the sorting sequence of materials in the same time window. Cost function was designed to improve the greedy strategy considering the risk of missing materials in the sorting, which enhances the practicality of the algorithm. Simulation environment was designed to simulate the algorithm, and the sorting experiment was carried out using the designed robot platform to verify the feasibility and effectiveness of the algorithm. Experiments show that the algorithm can plan an effective sorting path in the actual sorting operation of the robot. The average sorting distance and sorting time are both smaller than the sequence planning algorithm, which improves the efficiency of robot sorting for continuous moving materials in the plane. The algorithm, with good real-time performance and strong practicability, has certain guiding significance for the research on the optimization of the sorting path in the case of dynamic sorting with Cartesian robot.