Research on differential Positioning technology of mobile Robot based on UWB

Zheng, Lei; Ai, Changsheng; Qi, Zhengguang; Geng, Dunyang; Feng, Zhiquan; Wang, Honglin

doi:10.1145/3501409.3501449

Cited by 2 publications

(3 citation statements)

References 6 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…E [8] and others chose OpenCV to identify and locate strawberry images. Wang [9] and others used OpenCV cascade classifier and monocular vision ranging counting to detect and locate the target fruit. Saini [10] and others developed a classifier based on deep convolutional neural network (DCNN) to make correct disease prediction in the early stage.…”

Section: Improved Hsv and Morphological Methods For Citrus Recognitio...mentioning

confidence: 99%

Citrus objects recognition in orchard scene using HSV methods

Hua,

Wu,

Liang

et al. 2024

International Conference on Image Processing and Artificial Intelligence (ICIPAl 2024)

View full text Add to dashboard Cite

There is a problem that it is always difficult for picking and spraying robots to identify the objects for such factors such as leaf occlusion, similar color and others. In this paper, based on the citrus image data set collected from the actual orchard scene, image features are extracted and a mathematical model is constructed to identify and count the number of citruses in each image, and the distribution of apples in the whole data set is displayed. A model is constructed to be used to identify and count citrus via these images with diversity of citrus colors and the complexity of the background. Firstly, the yellow mature citruses are focused on using the HSV (Hue, Saturation, Value) method for the data sets. Secondly, the empirical HSV range for two citrus fruits, cyan and yellow, was defined, and contour processing is introduced to optimize the recognition model to process more citrus image datasets. Finally, such three types of objects as immature citrus, leaves with similar colors, and citrus covered by leaves are distinguish. The research results indicate that we adopt more detailed color threshold settings and morphological operations with the eccentricity of the contour is less than 0.85, and can distinguish citrus and leaves through image segmentation,and the recognition effect on citrus objects is improved.

show abstract

Section: Improved Hsv and Morphological Methods For Citrus Recognitio...mentioning

confidence: 99%

Citrus objects recognition in orchard scene using HSV methods

Hua,

Wu,

Liang

et al. 2024

International Conference on Image Processing and Artificial Intelligence (ICIPAl 2024)

View full text Add to dashboard Cite

show abstract

“…These properties make UWB sensors extremely useful for robotic navigation as robots can use them to measure ranges to reference points (also equipped with UWB sensors). UWB sensors have been used to either localize a robot directly or cure the drift caused by unavoidable accumulative errors [5], [6], [7], [8], [9], [10].…”

Section: Introductionmentioning

confidence: 99%

“…Related works UWB ranging has been widely studied for robotic applications thanks to its fine-grained ranges. Zheng et al [6] utilize a UWB-mesh network for mobile robot localization. Tiemann et al [7] use UWB sensors along with a camera to enhance monocular SLAM for a UAV in indoor environments.…”

Section: Introductionmentioning

confidence: 99%

DeepCIR: Insights into CIR-based Data-driven UWB Error Mitigation

Tran

Dai

Trigoni

et al. 2022

2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

View full text Add to dashboard Cite

Ultra-Wide-Band (UWB) ranging sensors have been widely adopted for robotic navigation thanks to their extremely high bandwidth and hence high resolution. However, off-the-shelf devices may output ranges with significant errors in cluttered, severe non-line-of-sight (NLOS) environments. Recently, neural networks have been actively studied to improve the ranging accuracy of UWB sensors using the channelimpulse-response (CIR) as input. However, previous works have not systematically evaluated the efficacy of various packet types and their possible combinations in a two-way-ranging transaction, including poll, response and final packets. In this paper, we firstly investigate the utility of different packet types and their combinations when used as input for a neural network. Secondly, we propose two novel data-driven approaches, namely FMCIR and WMCIR, that leverage two-sided CIRs for efficient UWB error mitigation. Our approaches outperform state-of-the-art by a significant margin, further reducing range errors up to 45%. Finally, we create and release a dataset of transaction-level synchronized CIRs (each sample consists of the CIR of the poll, response and final packets), which will enable further studies in this area.

show abstract

Research on differential Positioning technology of mobile Robot based on UWB

Cited by 2 publications

References 6 publications

Citrus objects recognition in orchard scene using HSV methods

Citrus objects recognition in orchard scene using HSV methods

DeepCIR: Insights into CIR-based Data-driven UWB Error Mitigation

Contact Info

Product

Resources

About