Homing with stereovision

Nirmal, Paramesh; Lyons, Damian M.

doi:10.1017/s026357471500034x

Cited by 15 publications

(14 citation statements)

References 23 publications

(32 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The key reason for the transition from the previous centers (γ = 0) to a dissipative dynamics with stable and unstable fixed points is the emergence of the term with cos(z) on the r.h.s. of equation (23). It is proportional to the radial velocityṙ and vanishes for γ = 0.…”

Section: A the Deterministic Casementioning

confidence: 95%

Search and return model for stochastic path integrators

Noetel

Freitas

Macau

et al. 2018

Chaos: An Interdisciplinary Journal of Nonlinear Science

View full text Add to dashboard Cite

1 arXiv:1807.11261v1 [cond-mat.stat-mech] 30 Jul 2018We extend a recently introduced prototypical stochastic model describing uniformly the search and return of objects looking for new food sources around a given home.The model describes the kinematic motion of the object with constant speed in two dimensions. The angular dynamics is driven by noise and describes a "pursuit" and "escape" behavior of the heading and the position vectors. Pursuit behavior ensures the return to the home and the escaping between the two vectors realizes exploration of space in the vicinity of the given home. Noise is originated by environmental influences and during decision making of the object. We take symmetric α-stable noise since such noise is observed in experiments. We now investigate for the simplest possible case, the consequences of limited knowledge of the position angle of the home. We find that both noise type and noise strength can significantly increase the probability of returning to the home. First, we review shortly main findings of the model presented in the former manuscript. These are the stationary distance distribution of the noise driven conservative dynamics and the observation of an optimal noise for finding new food sources. Afterwards, we generalize the model by adding a constant shift γ within the interaction rule between the two vectors. The latter might be created by a permanent uncertainty of the correct home position. Non vanishing shifts transform the kinematics of the searcher to a dissipative dynamics. For the latter we discuss the novel deterministic properties and calculate the stationary spatial distribution around the home.

show abstract

Section: A the Deterministic Casementioning

confidence: 95%

Search and return model for stochastic path integrators

Noetel

Freitas

Macau

et al. 2018

Chaos: An Interdisciplinary Journal of Nonlinear Science

View full text Add to dashboard Cite

show abstract

“…The advantage of using depth information is that it provides an estimate of how far to move in addition to which direction to move. It has been shown 7,24,25 Table I. Notations used in visual homing formulas.…”

Section: Prior Literaturementioning

confidence: 99%

“…All the stereovision homing experiments in ref. [7] were conducted with the commonly available Bumblebee2 stereo-camera with 66 • FOV. Wide FOV stereo images were obtained by concatenating (not stitching) multiple visual and depth images.…”

Section: Symbolmentioning

confidence: 99%

“…Recall that while visual homing using depth from stereo-vision has better performance than depth from scale, 7 which in turn has shown better performance than not using depth information at all. 6 However, restricting the FOV may arguably lead to a decrease in performance.…”

Section: Fovmentioning

confidence: 99%

“…5 It has been shown that visual homing performs better when depth-related cues are included, 6 for example, using a stereo-camera. 7 It is typical to assume a panoramic field of view (FOV) for visual homing. 8 While panoramic stereo-camera technology is available, 9,10 it is a specialized technology, and the typical stereo-cameras (and more recently RGB-D cameras) used in robotics have a limited FOV.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Evaluation of Field of View Width in Stereo-vision-Based Visual Homing

Lyons¹,

Barriage²,

Signore³

2019

Robotica

View full text Add to dashboard Cite

SummaryVisual homing is a local navigation technique used to direct a robot to a previously seen location by comparing the image of the original location with the current visual image. Prior work has shown that exploiting depth cues such as image scale or stereo-depth in homing leads to improved homing performance. While it is not unusual to use a panoramic field of view (FOV) camera in visual homing, it is unusual to have a panoramic FOV stereo-camera. So, while the availability of stereo-depth information may improve performance, the concomitant-restricted FOV may be a detriment to performance, unless specialized stereo hardware is used. In this paper, we present an investigation of the effect on homing performance of varying the FOV widths in a stereo-vision-based visual homing algorithm using a common stereo-camera. We have collected six stereo-vision homing databases – three indoor and three outdoor. Based on over 350,000 homing trials, we show that while a larger FOV yields performance improvements for larger homing offset angles, the relative improvement falls off with increasing FOVs, and in fact decreases for the widest FOV tested. We conduct additional experiments to identify the cause of this fall-off in performance, which we term the ‘blinder’ effect, and which we predict should affect other correspondence-based visual homing algorithms.

show abstract