Iconic memory-based omnidirectional route panorama navigation

Yagi, Yasushi; Imai, K.; Yachida, Masahiko

doi:10.1109/robot.2003.1241654

Cited by 14 publications

(15 citation statements)

References 18 publications

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“…In [4] these images are used for storing iconically the spatio-temporal route and then using it for navigation. A different approach is to use the information of 1-D images in a reactive way.…”

Section: Introductionmentioning

confidence: 99%

Robot navigation behaviors based on omnidirectional vision and information theory

Bonev¹,

Quevedo²,

Ruíz³

2007

jopha

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Abstract-In this work we present a reactive autonomous robot navigation system based only on omnidirectional vision. It does not rely on any prior knowledge about the environment apart from assuming a structured one, like indoor corridors or outdoor avenues. The direction of the corridor is estimated from the entropy analysis of a 1-D omnidirectional image. The 2-D omnidirectional image is analyzed for obstacle avoidance and for keeping a safety distance from the borders of the corridor. Both methods are non-metric and no 3-D information is needed. The system performs well with different resolutions and the catadioptric sensor needs no calibration. We present results from indoor and outdoor experiments.

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Section: Introductionmentioning

confidence: 99%

Robot navigation behaviors based on omnidirectional vision and information theory

Bonev¹,

Quevedo²,

Ruíz³

2007

jopha

View full text Add to dashboard Cite

show abstract

“…A mono-vision or ceiling-vision SLAM approach, using images obtained from a single camera, estimates the current location of a robot based on the coordinates of the feature points obtained by comparing the previous frame with the current one [21]- [26]. This requires a comparison of the feature corners and boundaries without other information, but it is difficult to determine the correlations.…”

Section: Extraction Of Feature Points Using Lkof Methodsmentioning

confidence: 99%

Multi-robot Mapping Using Omnidirectional-Vision SLAM Based on Fisheye Images

Choi

Kwon

Lee

et al. 2014

ETRI J

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This paper proposes a global mapping algorithm for multiple robots from an omnidirectional-vision simultaneous localization and mapping (SLAM) approach based on an object extraction method using LucasKanade optical flow motion detection and images obtained through fisheye lenses mounted on robots. The multi-robot mapping algorithm draws a global map by using map data obtained from all of the individual robots. Global mapping takes a long time to process because it exchanges map data from individual robots while searching all areas. An omnidirectional image sensor has many advantages for object detection and mapping because it can measure all information around a robot simultaneously. The process calculations of the correction algorithm are improved over existing methods by correcting only the object's feature points. The proposed algorithm has two steps: first, a local map is created based on an omnidirectional-vision SLAM approach for individual robots. Second, a global map is generated by merging individual maps from multiple robots. The reliability of the proposed mapping algorithm is verified through a comparison of maps based on the proposed algorithm and real maps.

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“…In practice, omnidirectional cameras are often utilized in many applications, like autonomous mobile robot (Yagi et al, 2005), video conference (Wallhoff et al, 2004), military purpose (Boult et al, 2001), virtual reality (Ikeuchi et al, 2004), collaboration with PTZ camera (Scotti et al, 2005) (Scotti et al, 2004), visual tracking. The techniques for detection and tracking using an omnidirectional camera can be grouped into two categories, one in warping space and the other in unwarping space.…”

Section: Related Workmentioning

confidence: 99%

Human Tracking by Importance Sampling Particle Filtering on Omnidirectional Camera Platform

Song

Huang

2008

IFAC Proceedings Volumes

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This paper proposes a sequential importance sampling (SIS) particle filtering framework to track the human with overcoming the warping and low resolution. We utilize a foreground-based importance sampling mechanism for efficiently converge to the target distribution. We construct a tracking system with the fusion image likelihood, even the human raises the head. Furthermore, the two-space integration to evaluate the likelihood measurement is proposed to robustly track human for overcome the warping effect. The overall performance has been validated in the experiments.

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Iconic memory-based omnidirectional route panorama navigation

Cited by 14 publications

References 18 publications

Robot navigation behaviors based on omnidirectional vision and information theory

Robot navigation behaviors based on omnidirectional vision and information theory

Multi-robot Mapping Using Omnidirectional-Vision SLAM Based on Fisheye Images

Human Tracking by Importance Sampling Particle Filtering on Omnidirectional Camera Platform

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