[논문]Loop Closure Detection Based on Differentiable Manifold

Dong, Tianzhen; Xue, Bin; Zhang, Qing; Zhao, Yuepeng; Li, Wenju; Li, Mengying

doi:10.1155/2022/4373064

Loop Closure Detection Based on Differentiable Manifold 원문보기

Mobile information systems : An international journal, v.2022, 2022년, pp.1 - 15

Dong, Tianzhen (School of Computer and Information Engineering, Shanghai Institute of Technology, Shanghai201400, China) , Xue, Bin (School of Computer and Information Engineering, Shanghai Institute of Technology, Shanghai201400, China) , Zhang, Qing (School of Computer and Information Engineering, Shanghai Institute of Technology, Shanghai201400, China) , Zhao, Yuepeng (School of Computer and Information Engineering, Shanghai Institute of Technology, Shanghai201400, China) , Li, Wenju (School of Computer and Information Engineering, Shanghai Institute of Technology, Shanghai201400, China) , Li, Mengying (School of Computer and Information Engineering, Shanghai Institute of Technology, Shanghai201400, China)

Abstract ▼ AI-Helper

Loop closure detection is an important part of SLAM (simultaneous location and mapping), which can effectively reduce the cumulative error of the system after long period of exploration. The existing loop closure detection methods are mainly to evenly distribute the accumulated error in the robot trajectory, but the motion error of the actual robot is also related to its motion speed and rotation angle, while the corrected motion trajectory of the robot is difficult to match the real trajectory. Based on the analysis of the mechanism of robot motion error, this paper proposes a novel loop closure detection method based on differentiable manifold, which mainly includes real-time pose based on manifold tangent space and smooth motion trajectory model of robot based on differential geometry. Firstly, we introduce the Frenet framework structure and establish the corresponding manifold tangent space theory for the keyframe pose nodes. The real-time problem of robot motion is equivalent to the problem of finding the optimal angle tangent vector. Secondly, the motion speed between keyframes is used to determine the characteristics of the robot motion trajectory. We calculate the curvature and torsion of the curve composed of several nodes based on the manifold tangent space and then combine the curve interpolation and ﬁtting of the keyframe nodes to achieve the approximation of the robot motion trajectory, and the smooth curve of the robot trajectory is obtained. Finally, the experiment veriﬁes that the method in this paper can effectively ensure the continuity and smoothness of the robot’s trajectory, thereby reducing the cumulative error of the system and improving the accuracy of loop closure detection.

참고문헌 (53)

Durrant-Whyte, H., Bailey, T.. Simultaneous localization and mapping: part I. IEEE robotics & automation magazine, vol.13, no.2, 99-110.

상세보기
Simultaneous Localization and Mapping, Underwater SLAM for Structured Environments Using an Imaging Sonar D. Ribas 2010 10.1007/978-3-642-14040-2
Lowry, Stephanie, Sunderhauf, Niko, Newman, Paul, Leonard, John J., Cox, David, Corke, Peter, Milford, Michael J.. Visual Place Recognition: A Survey. IEEE transactions on robotics : a publication of the IEEE Robotics and Automation Society, vol.32, no.1, 1-19.

상세보기
Methods for Appearance-Based Loop Closure Detection: Applications to Topological Mapping and Image Mosaicking E. Garcia-Fidalgo 2018 10.1007/978-3-319-75993-7
X. Gao Ldso: direct sparse odometry with loop closure
Cummins, Mark, Newman, Paul. FAB-MAP: Probabilistic Localization and Mapping in the Space of Appearance. The International journal of robotics research, vol.27, no.6, 647-665.

상세보기
Angeli, A., Filliat, D., Doncieux, S., Meyer, J.-A.. Fast and Incremental Method for Loop-Closure Detection Using Bags of Visual Words. IEEE transactions on robotics : a publication of the IEEE Robotics and Automation Society, vol.24, no.5, 1027-1037.

상세보기
D. G´alvez-L´opez Real-time loop detection with bags of binary words
Galvez-López, D., Tardos, J. D.. Bags of Binary Words for Fast Place Recognition in Image Sequences. IEEE transactions on robotics : a publication of the IEEE Robotics and Automation Society, vol.28, no.5, 1188-1197.

상세보기
J. Engel 10.1007/978-3-319-10605-2_54 Lsd-slam: large-scale direct monocular slam

상세보기
Karakasis, E.G., Amanatiadis, A., Gasteratos, A., Chatzichristofis, S.A.. Image moment invariants as local features for content based image retrieval using the Bag-of-Visual-Words model. Pattern recognition letters, vol.55, 22-27.

상세보기
Kejriwal, N., Kumar, S., Shibata, T.. High performance loop closure detection using bag of word pairs. Robotics and autonomous systems, vol.77, 55-65.

상세보기
10.1109/icra.2012.6224623
10.1109/icra.2017.7989671
Bampis, Loukas, Amanatiadis, Angelos, Gasteratos, Antonios. Fast loop-closure detection using visual-word-vectors from image sequences. The International journal of robotics research, vol.37, no.1, 62-82.

상세보기
10.23919/eusipco.2018.8553252
10.1109/iros.2014.6943207
10.1109/icra.2018.8461146
J. Chen A compact loop closure detection based on spatial partitioning
Robotics and Autonomous Systems P. Valigi 53 Robust visual semi-semantic loop closure detection by a covisibility graph and cnn features
R. Finman Toward Object-Based Place Recognition in Dense Rgb-D Maps
S. An Fast and Incremental Loop Closure Detection Using Proximity Graphs
Liang, Zhiwei, Wang, Chengzhi. A Semi-Direct Monocular Visual SLAM Algorithm in Complex Environments. Journal of intelligent & robotic systems, vol.101, no.1, 25-.

상세보기
P. Siva Looking beyond the image: unsupervised learning for object saliency and detection
Le, T. Hoang Ngan, Luu, Khoa, Zhu, Chenchen, Savvides, Marios. Semi self-training beard/moustache detection and segmentation simultaneously. Image and vision computing, vol.58, 214-223.

상세보기
C. Liu 1280
P. Zhou Learning rich features for image manipulation detection
10.1109/iros.2016.7759685
Autonomous Robots G. Xiang Unsupervised learning to detect loops using deep neural networks for visual slam system
K. Konda 10.5220/0005299304860490 Learning visual odometry with a convolutional network
Costante, Gabriele, Mancini, Michele, Valigi, Paolo, Ciarfuglia, Thomas A.. Exploring Representation Learning With CNNs for Frame-to-Frame Ego-Motion Estimation. IEEE robotics and automation letters, vol.1, no.1, 18-25.

상세보기
Y. Xia An evaluation of deep learning in loop closure detection for visual slam
10.1109/chicc.2015.7260555
10.1109/ICRA40945.2020.9196764
P. Geneva An efficient schmidt-ekf for 3d visualinertial slam
Lowe, David G.. Distinctive Image Features from Scale-Invariant Keypoints. International journal of computer vision, vol.60, no.2, 91-110.

상세보기
H. Bay Surf: speeded up robust features
E. Rublee 10.1109/ICCV.2011.6126544 Orb: an efficient alternative to sift or surf
IEEE Transactions on Robotics R. Mur-Artal 10.1109/TRO.2017.2705103 Orb-slam2: an open-source slam system for monocular, stereo, and rgb-d cameras
P. Protzel Brief-gist - closing the loop by simple means
Oliva, Aude; Torralba, Antonio etc. "Modeling the Shape of the Scene: A Holistic Representation of the Spatial Envelope." International journal of computer vision, v.42 no.3 (2001), pp. 145-175, doi:10.1023/A:1011139631724.
Nourani-Vatani, Navid, Borges, Paulo Vinicius Koerich, Roberts, Jonathan M., Srinivasan, Mandyam V.. On the Use of Optical Flow for Scene Change Detection and Description. Journal of intelligent & robotic systems, vol.74, no.3, 817-846.

상세보기
T. Naseer 10.1609/aaai.v28i1.9057 Robust visual robot localization across seasons using network flows

상세보기
Negre Carrasco, Pep Lluis, Bonin-Font, Francisco, Oliver-Codina, Gabriel. Global image signature for visual loop-closure detection. Autonomous robots, vol.40, no.8, 1403-1417.

상세보기
The Visual Computer O. Guclu 10.1007/s00371-019-01720-8 Integrating global and local image features for enhanced loop closure detection in rgb-d slam systems
L. Bampis 10.1109/IROS.2016.7759667 Encoding the description of image sequences: a two-layered pipeline for loop closure detection
10.1109/iros.2012.6385773
R. Arroyo Towards life-long visual localization using an efficient matching of binary sequences from images
Gawel, Abel, Don, Carlo Del, Siegwart, Roland, Nieto, Juan, Cadena, Cesar. X-View: Graph-Based Semantic Multiview Localization. IEEE robotics and automation letters, vol.3, no.3, 1687-1694.

상세보기
Wang, Yuwei, Qiu, Yuanying, Cheng, Peitao, Duan, Xuechao. Robust Loop Closure Detection Integrating Visual-Spatial-Semantic Information via Topological Graphs and CNN Features. Remote sensing, vol.12, no.23, 3890-.

상세보기
Gao, Peng, Zhang, Hao. Long-Term Loop Closure Detection through Visual-Spatial Information Preserving Multi-Order Graph Matching. Proceedings of the ... aaai conference on artificial intelligence, vol.34, no.6, 10369-10376.

상세보기
Bundle Adjustment - a Modern Synthesis B. Triggs 10.1007/3-540-44480-7_21
T. Schps Bad slam: bundle adjusted direct rgb-d slam

내보내기 구분	파일저장 인쇄 메일전송
구성항목	기본정보 상세정보 관리번호, 논문명, 저널/프로시딩명, 저자 , 발행년, 권, 호, 시작페이지, 끝페이지, 발행기관 관리번호, 논문명, 대등논문명, 저자 , 저널/프로시딩명, 발행기관, 발행년, 발행언어, 권, 호, 시작페이지, 끝페이지, ISBN, ISSN, 주제분야, 키워드, 초록(한글), 초록(영문), 저자(소속기관)
저장형식	Text(ASCII format) Excel format RefWorks Direct Export RIS format (for Reference Manager, ProCite, EndNote), Scholar's Aids, Mendeley
메일정보	받는사람 (필수) @ 보내는사람 (선택) @ 제목 내용 KISTI 검색결과 이메일 서비스
안내	총 건의 자료가 검색되었습니다. 다운받으실 자료의 인덱스를 입력하세요. (1-10,000) 검색결과의 순서대로 최대 10,000건 까지 다운로드가 가능합니다. 데이타가 많을 경우 속도가 느려질 수 있습니다.(최대 2~3분 소요) 다운로드 파일은 UTF-8 형태로 저장됩니다. 파일의 내용이 제대로 보이지 않을실 때는 웹브라우저 상단의 보기 -> 인코딩 -> 자동선택 여부를 확인하십시오. ~ Text(ASCII format) Excel format

연합인증

Loop Closure Detection Based on Differentiable Manifold 원문보기

Abstract ▼ AI-Helper

참고문헌 (53)

이 논문을 인용한 문헌

관련 콘텐츠

원문 보기

원문 URL 링크

오픈액세스(OA) 유형

이 논문과 함께 이용한 콘텐츠

AI-Helper ※ AI-Helper는 오픈소스 모델을 사용합니다.

선택된 텍스트