Modified probabilistic laser sensor model to reduce the effect of the mixed pixel for robust autonomous mobile robot navigation

Ravinder Singh, K. S. Nagla
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Abstract

The reliable performance of the autonomous mobile robot depends upon the accuracy and reliability of the sensors. Mixed pixel problem is the consequence of the effects caused by diverse intrinsic and extrinsic parameters, impulse noise, variation in incident angle and beam width that reduce the reliability of the laser scanner that leads to generate uncertainty in sensory information. The objective of this study is to modify the laser sensor model by reducing the effect of the mixed pixel problem corresponding to incident angles and intensity by a newly designed algorithm - Edge Detection Technique (EDT) for laser scanner to generate an efficient mobile robot mapping for the robust autonomous navigation. Various real-world experiments have been performed to check the reliability of the proposed EDT algorithm linked with probabilistic laser sensor model fitted on a mobile robot and the obtained results are validated through qualitative and quantitative analysis corresponding to conventional approaches.
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改进的概率激光传感器模型以减少混合像素对鲁棒自主移动机器人导航的影响
自主移动机器人的可靠性能取决于传感器的准确性和可靠性。混合像素问题是由不同的内在和外在参数、脉冲噪声、入射角和光束宽度的变化引起的影响的结果,这些因素降低了激光扫描仪的可靠性,从而导致传感信息的不确定性。本研究的目的是通过一种新设计的激光扫描仪边缘检测技术(EDT)算法来修改激光传感器模型,减少与入射角和强度相对应的混合像素问题的影响,以生成一个高效的移动机器人地图,用于稳健的自主导航。已经进行了各种真实世界的实验来检查所提出的EDT算法与安装在移动机器人上的概率激光传感器模型的可靠性,并且通过与传统方法相对应的定性和定量分析来验证所获得的结果。
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来源期刊
International Journal of Vehicle Autonomous Systems
International Journal of Vehicle Autonomous Systems Engineering-Automotive Engineering
CiteScore
1.30
自引率
0.00%
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0
期刊介绍: The IJVAS provides an international forum and refereed reference in the field of vehicle autonomous systems research and development.
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