Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.14279/28947
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Hadjiloizou, Loizos | - |
dc.contributor.author | Makridis, Evagoras | - |
dc.contributor.author | Charalambous, Themistoklis | - |
dc.contributor.author | Deliparaschos, Kyriakos M. | - |
dc.date.accessioned | 2023-03-31T08:33:24Z | - |
dc.date.available | 2023-03-31T08:33:24Z | - |
dc.date.issued | 2023-06 | - |
dc.identifier.citation | 31st Mediterranean Conference on Control and Automation, 26-29 June, Limassol, Cyprus | en_US |
dc.identifier.uri | https://hdl.handle.net/20.500.14279/28947 | - |
dc.description.abstract | We present a multisensor fusion framework for the onboard real-time navigation of a quadrotor in an indoor environment. The framework integrates sensor readings from an Inertial Measurement Unit (IMU), a camera-based object detection algorithm, and an Ultra-WideBand (UWB) localisation system. Often the sensor readings are not always readily available, leading to inaccurate pose estimation and hence poor navigation performance. To effectively handle and fuse sensor readings, and accurately estimate the pose of the quadrotor for tracking a predefined trajectory, we design a Maximum Correntropy Criterion Kalman Filter (MCC-KF) that can manage intermittent observations. The MCC-KF is designed to improve the performance of the estimation process when is done with a Kalman Filter (KF), since KFs are likely to degrade dramatically in practical scenarios in which noise is non-Gaussian (especially when the noise is heavy-tailed). To evaluate the performance of the MCC-KF, we compare it with a previously designed Kalman filter by the authors. Through this comparison, we aim to demonstrate the effectiveness of the MCC-KF in handling indoor navigation missions. The simulation results show that our presented framework offers low positioning errors, while effectively handling intermittent sensor measurements. | en_US |
dc.format | en_US | |
dc.language.iso | en | en_US |
dc.subject | a Maximum Correntropy Criterion Kalman Filter | en_US |
dc.subject | Multisensor fusion framework | en_US |
dc.title | Maximum Correntropy Criterion Kalman Filter For Indoor Quadrotor Navigation Under Intermittent Measurements | en_US |
dc.type | Conference Papers | en_US |
dc.collaboration | Cyprus University of Technology | en_US |
dc.collaboration | KTH Royal Institute of Technology | en_US |
dc.collaboration | University of Cyprus | en_US |
dc.subject.category | Electrical Engineering - Electronic Engineering - Information Engineering | en_US |
dc.country | Cyprus | en_US |
dc.country | Sweden | en_US |
dc.subject.field | Engineering and Technology | en_US |
dc.publication | Peer Reviewed | en_US |
dc.relation.conference | Mediterranean Conference on Control & Automation (MED) | en_US |
dc.identifier.url | http://arxiv.org/abs/2303.09561v1 | - |
cut.common.academicyear | 2022-2023 | en_US |
item.openairecristype | http://purl.org/coar/resource_type/c_c94f | - |
item.openairetype | conferenceObject | - |
item.cerifentitytype | Publications | - |
item.grantfulltext | open | - |
item.languageiso639-1 | en | - |
item.fulltext | With Fulltext | - |
crisitem.author.dept | Department of Electrical Engineering, Computer Engineering and Informatics | - |
crisitem.author.faculty | Faculty of Engineering and Technology | - |
crisitem.author.orcid | 0000-0003-0618-5846 | - |
crisitem.author.parentorg | Faculty of Engineering and Technology | - |
Appears in Collections: | Δημοσιεύσεις σε συνέδρια /Conference papers or poster or presentation |
Files in This Item:
File | Size | Format | |
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2303.09561.pdf | 658.16 kB | Adobe PDF | View/Open |
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