Enhanced Positioning Systems Using Optical Mouse Sensors

He, Mingxiao; Guo, Xuemei; Wang, Guoli

doi:10.1007/978-3-319-13963-0_47

Cited by 4 publications

(4 citation statements)

References 7 publications

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“…Some works explore the use of optical mouse sensors for developing positioning systems. In [12], a low-cost customized optical sensor is proposed where, an adaptation mechanism for enhancing the robustness to surface height variations and a novel calibration paradigm with fiducial landmarks used for mitigating the cumulative errors have been developed. Their prototype uses three optical mouse sensor units located at different heights along a slideway.…”

Section: Related Workmentioning

confidence: 99%

A Vision-Based Odometer for Localization of Omnidirectional Indoor Robots

Patruno

Colella

Nitti

et al. 2020

Sensors

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In this paper we tackle the problem of indoor robot localization by using a vision-based approach. Specifically, we propose a visual odometer able to give back the relative pose of an omnidirectional automatic guided vehicle (AGV) that moves inside an indoor industrial environment. A monocular downward-looking camera having the optical axis nearly perpendicular to the ground floor, is used for collecting floor images. After a preliminary analysis of images aimed at detecting robust point features (keypoints) takes place, specific descriptors associated to the keypoints enable to match the detected points to their consecutive frames. A robust correspondence feature filter based on statistical and geometrical information is devised for rejecting those incorrect matchings, thus delivering better pose estimations. A camera pose compensation is further introduced for ensuring better positioning accuracy. The effectiveness of proposed methodology has been proven through several experiments, in laboratory as well as in an industrial setting. Both quantitative and qualitative evaluations have been made. Outcomes have shown that the method provides a final positioning percentage error of 0.21% on an average distance of 17.2 m. A longer run in an industrial context has provided comparable results (a percentage error of 0.94% after about 80 m). The average relative positioning error is about 3%, which is still in good agreement with current state of the art.

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Section: Related Workmentioning

confidence: 99%

A Vision-Based Odometer for Localization of Omnidirectional Indoor Robots

Patruno

Colella

Nitti

et al. 2020

Sensors

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“…Figure 14 shows two views of the same slope before and after the 2011 heavy rainfall in the mountains of RJ state that killed hundreds of people and dislodged thousands, predominantly in hilltops, steep slopes, areas surrounding lakes and riverbanks. The image on the left displays a region before the landslide and on the right after the 2011 heavy rainfall [24,[58][59][60]. Between the 24 h period from 11 to 12 January 2011, the rainfall exceeded what was projected for the entire month of January, so that flooding and landslides followed immediately.…”

Section: Case Study 1: Mudslides In Mountainous Region Of Rio De Janementioning

confidence: 99%

“…They have an inbuilt camera to acquire images from the surface underneath the sensor. Each OMIC was placed at a different height, with a large carefully selected focal length lens and intense illumination to work stably at a given distance from its work surface [59].…”

Section: Experiments 1: System With Omics For Displacement Estimationmentioning

confidence: 99%

Emergency Response Cyber-Physical Framework for Landslide Avoidance with Sustainable Electronics †

et al. 2018

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An Emergency Response (ER) Cyber-Physical System (CPS) to avoid landslides and survey areas located on or near slopes is introduced that handles two problems: electronic waste disposal, and environmental disasters. Uncomplicated detection circuits using salvaged components can pinpoint floods in impoverished regions. CPSs simplify hazard prediction and mitigation in disaster supervision. Nonetheless, few green practices and efforts have been accomplished in this regard. Recent technical advances help landslides studies and the evaluation of suitable risk alleviation measures. This work addresses in situ meters, and cameras to observe ground movements more accurately. The ER-CPS identifies and can help mitigate landslides using techniques based on motion detection that can productively predict and monitor the zone conditions to classify it, and the landslide-related data can be transmitted to inspecting stations to lessen the erosion/sedimentation likelihood while increasing security.

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“…Bonarini et al [14] used a pair of optical mice using a dead reckoning procedure to ensure accurate odometrical measurements on mobile robots. He et al [15] developed a positioning system to increase the odometrical measurements on mobile devices. The study investigated an adaptation mechanism that could reduce the effects of height variations between the optical mouse and a surface.…”

Section: Introductionmentioning

confidence: 99%

The implementation of an optical computer mouse as a low-cost displacement sensor

Dharmalingum,

Padaychee

2023

MATEC Web Conf.

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The accurate measurement of distance, position or displacement is a requirement in many robotics projects. This paper presents the investigation of a HP M-UAE96 optical mouse as a low-cost displacement sensor. Various resolutions were obtained on a Windows operating system in conjunction with MATLAB®. The Arduino IDE was used with a linear actuator module to accurately produce predetermined linear movements. The most suitable resolution was found to be 0.2 mm/pixel and was implemented on a parallel kinematic manipulator in a case study. Surface contact and length of measurement were significant factors that influenced measurement accuracy.

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Enhanced Positioning Systems Using Optical Mouse Sensors

Cited by 4 publications

References 7 publications

A Vision-Based Odometer for Localization of Omnidirectional Indoor Robots

A Vision-Based Odometer for Localization of Omnidirectional Indoor Robots

Emergency Response Cyber-Physical Framework for Landslide Avoidance with Sustainable Electronics †

The implementation of an optical computer mouse as a low-cost displacement sensor

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