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基于多模态数据和粒子滤波器的移动机器人目标跟踪方法

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在复杂环境中,目标可能受到遮挡、光照变化、背景干扰等因素的影响,导致移动机器人目标跟踪精度和效率低;为保证移动机器人目标跟踪效果,提出了基于多模态数据和粒子滤波器的移动机器人目标跟踪方法;采集移动机器人目标多模态数据,通过畸变校正、去噪、增强等步骤,完成移动机器人目标多模态数据的预处理;从边缘、颜色、纹理等多个方面,提取移动机器人目标多模态数据特征;以提取特征为研究对象,通过粒子滤波器的训练,得出移动机器人跟踪目标的检测结果,最终通过实时目标位置的更新,实现移动机器人目标跟踪;仿真结果表明,在单目标和多目标两种仿真场景下,设计方法的跟踪误差和跟踪时延较低,能够有效提高移动机器人目标跟踪精度和效率,具有较好的移动机器人目标跟踪效果。
Mobile Robot Target Tracking Method Based on Multimodal Data and Particle Filter
In complex environments,targets may be affected by factors such as occlusion,changes in lighting,and background in-terference,resulting in low tracking accuracy and efficiency of mobile robots.In order to ensure the effect of mobile robot target tracking,a mobile robot target tracking method based on multimodal data and particle filter is proposed.Collect the multimodal data of mobile robot targets,and complete the preprocessing of multimodal data of mobile robot targets through the steps of the distortion correction,denoising,and enhancement.The multimodal data features of mobile robot targets are extracted from multiple aspects such as edges,colors,and textures.Taking the extracted features as the research object,the detection results of the mobile robot tracking target are obtained through the training of the particle filter.Finally,the mobile robot target tracking is realized through the real-time target position update.The simulation results show that in both single target and multi target simulation scenarios,the de-signed method has low tracking error and tracking delay,which can effectively improve the accuracy and efficiency of mobile robot tar-get tracking,and has a good mobile robot target tracking performance.

multimodal dataparticle filtermobile robotstarget tracking

李强

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江苏安全技术职业学院,江苏徐州 221000

多模态数据 粒子滤波器 移动机器人 目标跟踪

2024

计算机测量与控制
中国计算机自动测量与控制技术协会

计算机测量与控制

CSTPCD
影响因子:0.546
ISSN:1671-4598
年,卷(期):2024.32(2)
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