基于视觉的SCARA臂智能路径规划

Yogesh Gautam , Bibek Prajapati , Sandeep Dhakal , Bibek Pandeya , Bijendra Prajapati
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引用次数: 2

摘要

提出了一种将目标检测与势场算法相结合的SCARA机械臂自主操作算法。通过retanet模型定位和检测起始、障碍和目标状态。该模型使用标准的预训练权重作为检查点,并使用SCARA手臂工作环境中的图像进行训练。然后,势场算法根据目标检测模型的结果,规划从起点到目标状态的合适路径,避免障碍状态。该算法在实际样机上进行了测试,结果令人满意。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Vision-based intelligent path planning for SCARA arm

This paper proposes a novel algorithm combining object detection and potential field algorithm for autonomous operation of SCARA arm. The start, obstacles, and goal states are located and detected through the RetinaNet Model. The model uses standard pre-trained weights as checkpoints which is trained with images from the working environment of the SCARA arm. The potential field algorithm then plans a suitable path from start to goal state avoiding obstacle state based on results from the object detection model. The algorithm is tested with a real prototype with promising results.

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CiteScore
8.40
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