The paper discusses the difficulty of balancing efficiency, power use, and safety for parallel robot arms doing multi-objective, ongoing grasping work during express delivery sorting and packaging. It provides a study on multi-objective grasping path planning for parallel robotic arms in express delivery sorting and packaging. Firstly, establish the kinematics model and workspace constraints of the parallel robotic arm. A multi-objective grasping task model is created by taking into account the spatial distribution and posture characteristics of express parcels. Secondly, we create a multi-objective optimization index system that includes grasping time, path length, system energy usage, and collision danger. Grasping sequence and trajectory planning are incorporated into the multi-objective optimization framework. In order to deal with the nonlinearity and multiple constraints of the problem, an improved NSGA-II-based multi-objective path planning method is proposed, and a collaborative optimization method for grasping sequence and path is introduced to improve the overall sorting efficiency. Then, it is validated in a simulation environment and compared to traditional single-objective planning methods and multi-objective particle swarm optimization algorithms. The experimental results show that the proposed method has better overall performance in important indicators such as grasping time, energy consumption, and path smoothness. Lastly, experiments were carried out on a real-world express sorting platform, which confirmed the feasibility and robustness of the algorithm in complex engineering settings. The research findings give a theoretical basis and technical backing for the effective application of parallel robotic arms in smart logistics and express sorting.
Hu et al. (Thu,) studied this question.
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