Path Optimization for Palletizing Robot by Integrating Improved RRT&#x0002A; with Multi-strategy Particle Swarm Algorithm

HUANG Kai; LI Fangli

doi:10.19554/j.cnki.1001-3563.2026.05.016

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Packaging Engineering ›› 2026, Vol. 47 ›› Issue (5) : 144-155. DOI: 10.19554/j.cnki.1001-3563.2026.05.016

Automatic and Intelligent Technology

Path Optimization for Palletizing Robot by Integrating Improved RRT* with Multi-strategy Particle Swarm Algorithm

HUANG Kai^*, LI Fangli

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Abstract

The work aims to optimize both obstacle avoidance path planning and motion trajectory of palletizing robots so as to address the issues of insufficient obstacle avoidance path planning and motion efficiency in palletizing robots during operation. Firstly, the motion trajectory of a palletizing robot was constructed using quintic B-spline curves. A two-stage RRT* algorithm was proposed for obstacle avoidance path planning. In the exploration phase, a heuristic sampling strategy and a priority queue strategy were introduced to enhance search efficiency. In the optimization phase, an anytime cost updating mechanism was adopted to accelerate the convergence to the optimal path. Based on the obtained collision-free path and with the goal of time optimality, a multi-strategy improved particle swarm optimization (PSO) algorithm was proposed to optimize the motion trajectory. This enhanced algorithm integrated a multimodal adaptive parameter adjustment mechanism, a quantum-behaved enhancement strategy, and a hierarchical elite learning strategy to optimize the motion trajectory of the palletizing robot. Experimental results demonstrated that the two-stage RRT* algorithm successfully guided the palletizing robot from the start point to the target point without collision, outperforming both the traditional RRT and an improved RRT algorithm in terms of search efficiency and path length. After optimization by the multi-strategy improved PSO algorithm, the total motion time of the palletizing robot was reduced to 37.42 s. Compared with the adaptive weight PSO and the standard PSO algorithms, the motion efficiency was improved by 23.29% and 26.41%, respectively. In conclusion, the synergistic application of the two-stage RRT* algorithm and the multi-strategy improved PSO algorithm generates a feasible and efficient operational path for the palletizing robot, ensuring obstacle avoidance safety while significantly shortening the motion time.

Key words

palletizing robot / obstacle avoidance path optimization / trajectory optimization / particle swarm algorithm / RRT*

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HUANG Kai, LI Fangli. Path Optimization for Palletizing Robot by Integrating Improved RRT* with Multi-strategy Particle Swarm Algorithm[J]. Packaging Engineering. 2026, 47(5): 144-155 https://doi.org/10.19554/j.cnki.1001-3563.2026.05.016

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