VPS-SLAM: Visual Planar Semantic SLAM for Aerial Robotic Systems
Autor: | Hriday Bavle, Paloma De La Puente, Jonathan P. How, Pascual Campoy |
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Přispěvatelé: | Ministerio de Economía y Competitividad (España), Bavle, Hriday, De La Puente, Paloma, How, Jonathan P., Campoy, Pascual, Bavle, Hriday [0000-0002-1732-0647], De La Puente, Paloma [0000-0002-8652-0300], How, Jonathan P. [0000-0001-8576-1930], Campoy, Pascual [0000-0002-9894-2009] |
Jazyk: | angličtina |
Rok vydání: | 2020 |
Předmět: |
Autonomous aerial robots
0209 industrial biotechnology General Computer Science Computer science 02 engineering and technology Simultaneous localization and mapping UAVs Electrical & electronics engineering [C06] [Engineering computing & technology] 020901 industrial engineering & automation Odometry Robustness (computer science) 0202 electrical engineering electronic engineering information engineering General Materials Science Computer vision Visual semantic SLAM Pose Visual SLAM Ingénierie électrique & électronique [C06] [Ingénierie informatique & technologie] business.industry General Engineering Mobile robot Object detection Visualization SLAM Robot Three-dimensional displays 020201 artificial intelligence & image processing lcsh:Electrical engineering. Electronics. Nuclear engineering Artificial intelligence business lcsh:TK1-9971 aerospace robotics distance measurement feature extraction graph theory mobile robots object detection pose estimation robot vision SLAM (robots) standard RGB-D dataset state of the art object detectors graph-based approach visual-inertial odometry low-level visual odometry lightweight visual semantic SLAM framework sparse semantic map complete 6DoF pose detected semantic objects planar surfaces geometrical information board aerial robotic platforms real-time visual semantic SLAM framework pose estimate high-level semantic information indoor environments aerial robotic systems visual planar semantic SLAM VPS-SLAM Semantics Detectors Data mining visual SLAM visual semantic SLAM autonomous aerial robots |
Zdroj: | Digital.CSIC. Repositorio Institucional del CSIC instname IEEE Access, Vol 8, Pp 60704-60718 (2020) |
Popis: | Indoor environments have abundant presence of high-level semantic information which can provide a better understanding of the environment for robots to improve the uncertainty in their pose estimate. Although semantic information has proved to be useful, there are several challenges faced by the research community to accurately perceive, extract and utilize such semantic information from the environment. In order to address these challenges, in this paper we present a lightweight and real-time visual semantic SLAM framework running on board aerial robotic platforms. This novel method combines low-level visual/visual-inertial odometry (VO/VIO) along with geometrical information corresponding to planar surfaces extracted from detected semantic objects. Extracting the planar surfaces from selected semantic objects provides enhanced robustness and makes it possible to precisely improve the metric estimates rapidly, simultaneously generalizing to several object instances irrespective of their shape and size. Our graph-based approach can integrate several state of the art VO/VIO algorithms along with the state of the art object detectors in order to estimate the complete 6DoF pose of the robot while simultaneously creating a sparse semantic map of the environment. No prior knowledge of the objects is required, which is a significant advantage over other works. We test our approach on a standard RGB-D dataset comparing its performance with the state of the art SLAM algorithms. We also perform several challenging indoor experiments validating our approach in presence of distinct environmental conditions and furthermore test it on board an aerial robot. This work was supported by the MISTI-Spain for the financial support in the project entitled Drone Autonomy and the Spanish Ministry of Economy and Competitivity for its funding Project (Complex Coordinated Inspection and Security missions by UAVs in cooperation with UGV) under Grant RTI2018-100847-B-C21. The work of Paloma de la Puente was supported in part by the Spanish Ministry of Economics and Competitivity under Grant DPI2017-86915-C3-3-R COGDRIVE. |
Databáze: | OpenAIRE |
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