15.3.2 Autonomous Vehicles, Low Level Image Processing

Chapter Contents (Back)
Autonomous Vehicle, Image Processing. Road Following.

Courtney, J.W., Magee, M.J., Aggarwal, J.K.,
Robot Guidance Using Computer Vision,
PR(17), No. 6, 1984, pp. 585-592.
Elsevier DOI BibRef 8400

Moravec, H.P.,
Sensor Fusion in Certainty Grids for Mobile Robots,
AIMag(9), No. 2, Summer 1988, pp. 61-74. Sensor Fusion. This combines stereo and sonar data or many different stereo computations to get better coverage and better results. BibRef 8800

Moravec, H.P.[Hans P.],
Robot Spatial Perception by Stereoscopic Vision and 3D Evidence Grids,
CMU-RI-TR-96-34, September 1996.
PS File. BibRef 9609

Acampora, A.S., and Winters, J.H.,
Three-Dimensional Ultrasonic Vision for Robotic Applications,
PAMI(11), No. 3, March 1989, pp. 291-303.
IEEE DOI Sonar Range Sensors. BibRef 8903

Kweon, I., and Kanade, T.,
High-Resolution Terrain Map from Multiple Sensor Data,
PAMI(14), No. 2, February 1992, pp. 278-292.
IEEE DOI Range Data, Registration. Track the ERIM data through the sequence to get a much better representation of the surface. Uses the existing DEM to reduce accumulation errors. BibRef 9202

Veatch, P.A., and Davis, L.S.,
Efficient Algorithms for Obstacle Detection Using Range Data,
CVGIP(50), No. 1, April 1990, pp. 50-74.
Elsevier DOI Find the drivable path from the ERIM range data. BibRef 9004

Yagi, Y., Kawato, S., Tsuji, S.,
Real-Time Omnidirectional Image Sensor (COPIS) for Vision-Guided Navigation,
RA(10), No. 1, February 1994, pp. 11-22.
See also Map-Based Navigation for a Mobile Robot with Omnidirectional Image Sensor COPIS. BibRef 9402

Yagi, Y.S.[Yasu-Shi], Yachida, M.[Masahiko],
Real-Time Omnidirectional Image Sensors,
IJCV(58), No. 3, July-August 2004, pp. 173-207.
DOI Link 0404

Yagi, Y., and Yachida, M.,
Real-Time Generation of Environmental Map and Obstacle Avoidance Using Omnidirectional Image Sensor with Conic Mirror,
IEEE DOI Panoramic Views. Camera, Conical Mirror. Horizon Vision. BibRef 9100

Yagi, Y.S.[Yasu-Shi], Imai, K.[Kousuke], Tsuji, K.[Kentaro], Yachida, M.[Masahiko],
Iconic Memory-Based Omnidirectional Route Panorama Navigation,
PAMI(27), No. 1, January 2005, pp. 78-87.
IEEE Abstract. 0412

Zhang, Z., Weiss, R., and Riseman, E.M.,
Feature Matching in 360^o Waveforms for Robot Navigation,
IEEE DOI Panoramic Views. Camera, Spherical Mirror. Horizon Vision. BibRef 9100

Hong, J.W., Tan, X., Pinette, B., Weiss, R., and Riseman, E.M.,
Image-Based Navigation Using 360^o Views,
DARPA90(782-791). Camera, Spherical Mirror. Horizon Vision. Discusses matching and navigation, but is really a sensor paper. A spherical mirror above the robot with a camera gets a circular view of the scene. Features on the rim of the scene are relatively stable. BibRef 9000

Talluri, R.K., and Aggarwal, J.K.,
Image/Map Correspondence for Mobile Robot Self-Location Using Computer Graphics,
PAMI(15), No. 6, June 1993, pp. 597-601.
IEEE DOI BibRef 9306
Positional Estimation of a Mobile Robot Using Edge Visibility Regions,
And: Find the position given a map of a polyhedral scene. BibRef

Talluri, R.K., Aggarwal, J.K.,
Mobile Robot Self-Location Using Model-Image Feature Correspondence,
RA(12), No. 1, February 1996, pp. 63-77. BibRef 9602

Talluri, R.K., Aggarwal, J.K.,
Position Estimation for an Autonomous Mobile Robot in an Outdoor Environment,
RA(8), 1992, pp. 573-584. BibRef 9200
Position Estimation for a Mobile Robot in an Unstructured Environment,
IROS90(159-166). BibRef

Talluri, R.K., Aggarwal, J.K.,
Positional Estimation Techniques for an Autonomous Mobile Robot: A Review,
(Univ. Texas, Austin) HPRCV92(Part 4, Chapter 4). BibRef 9200

del Bimbo, A., Landi, L., Santini, S.,
Dynamic Neural Estimation for Autonomous Vehicles Driving,
IEEE DOI BibRef 9200

Mitchell, J.S.B., Payton, D.W., Keirsey, D.M.,
Planning and Reasoning for Autonomous Vehicle Control,
IJIS(2), 1987, pp. 129-198. BibRef 8700

Daily, M.J., Harris, J.G., and Reiser, K.,
An Operational Perception System for Cross-Country Navigation,
DARPA88(568-575). BibRef 8800
And: CVPR88(794-802).
IEEE DOI The vision for the Hughes navigation system, range image mapping. BibRef

Turk, M.A., Morgenthaler, D.G., Gremban, K.D., and Marra, M.,
VITS--A Vision System for Autonomous Land Vehicle Navigation,
PAMI(10), No. 3, May 1988, pp. 342-361.
IEEE DOI Application, Navigation. BibRef 8805

Szabo, S., Coombs, D., Herman, M., Camus, T.A., Liu, H.C.,
A Real-Time Computer Vision Platform for Mobile Robot Applications,
RealTimeImg(2), No. 5, October 1996, pp. 315-327. 9611

Liaw, D.C., Chiang, H.H., Lee, T.T.,
Elucidating Vehicle Lateral Dynamics Using a Bifurcation Analysis,
ITS(8), No. 2, April 2007, pp. 195-207.

Bai, L.[Li], Wang, Y.[Yan],
A Sensor Fusion Framework Using Multiple Particle Filters for Video-Based Navigation,
ITS(11), No. 2, June 2010, pp. 348-358.

Bai, L.[Li], Wang, Y.[Yan],
Road tracking using particle filters with partition sampling and auxiliary variables,
CVIU(115), No. 10, October 2011, pp. 1463-1471.
Elsevier DOI 1108
Road tracking; Particle filter; Partition sampling BibRef

de Cristóforis, P.[Pablo], Nitsche, M.[Matias], Krajník, T.[Tomáš], Pire, T.[Taihú], Mejail, M.[Marta],
Hybrid vision-based navigation for mobile robots in mixed indoor/outdoor environments,
PRL(53), No. 1, 2015, pp. 118-128.
Elsevier DOI 1502
Vision-based navigation BibRef

Cira, C.I.[Calimanut-Ionut], Kada, M.[Martin], Manso-Callejo, M.Á.[Miguel-Ángel], Alcarria, R.[Ramón], Sanchez, B.B.[Borja Bordel],
Improving Road Surface Area Extraction via Semantic Segmentation with Conditional Generative Learning for Deep Inpainting Operations,
IJGI(11), No. 1, 2022, pp. xx-yy.
DOI Link 2201

Zhang, Y.G.[Yi-Gong], Xie, J.[Jin], Álvarez, J.M.[José M.], Xu, C.Z.[Cheng-Zhong], Yang, J.[Jian], Kong, H.[Hui],
Capitalizing on RGB-FIR Hybrid Imaging for Road Detection,
ITS(23), No. 8, August 2022, pp. 13819-13834.
Roads, Sensors, Finite impulse response filters, Laser radar, Cameras, Feature extraction, RGB-FIR fusion, road detection, CNN, hierarchical cross model BibRef

Kothandaraman, D.[Divya], Chandra, R.[Rohan], Manocha, D.[Dinesh],
SS-SFDA: Self-Supervised Source-Free Domain Adaptation for Road Segmentation in Hazardous Environments,
Training, Adaptation models, Rain, Roads, Minimization BibRef

Carton, F.[Florence], Filliat, D.[David], Rabarisoa, J.[Jaonary], Pham, Q.C.[Quoc Cuong],
Using Semantic Information to Improve Generalization of Reinforcement Learning Policies for Autonomous Driving,
WACVW21(144-151) Autonomous Vehicle Vision
Training, Semantics, Reinforcement learning, Task analysis, Autonomous vehicles BibRef

Song, K.T., Tai, J.C.,
Image-Based Turn Ratio Measurement at Road Intersection,
ICIP05(I: 1077-1080).

Wang, Z.P., Ge, S.S., Lee, T.H., Lai, X.C.,
Adaptive Smart Neural Network Tracking Control of Wheeled Mobile Robots,

Marino, F., Stella, E., Veneziani, N., Distante, A.,
Real time hardware architecture for visual robot navigation,
CIAP97(II: 93-100).
Springer DOI 9709

Aubert, D., and Thorpe, C.E.,
Color Image Processing for Navigation: Two Road Trackers,
CMU-RI-TR-90-09, April 1990. Color. BibRef 9004

Chapter on Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following continues in
Road, Path Following Operators .

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