Three-dimensional catadioptric vision sensor using omnidirectional dot matrix projection

Fuqiang Zhou; Xin Chen; Haishu Tan; Xinghua Chai

doi:10.3788/COL201614.111403

Journals >Chinese Optics Letters >Volume 14 >Issue 11 >Page 111403 > Article

Chinese Optics Letters
Vol. 14, Issue 11, 111403 (2016)

Three-dimensional catadioptric vision sensor using omnidirectional dot matrix projection

Fuqiang Zhou^1、*, Xin Chen¹, Haishu Tan², and Xinghua Chai¹

Author Affiliations

¹Key Laboratory of Precision Opto-mechatronics Technology, Ministry of Education, Beihang University, Beijing 100191, China

²Department of Electronic Information Engineering, Foshan University, Foshan 528000, China

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DOI: 10.3788/COL201614.111403 Cite this Article Set citation alerts

Fuqiang Zhou, Xin Chen, Haishu Tan, Xinghua Chai. Three-dimensional catadioptric vision sensor using omnidirectional dot matrix projection[J]. Chinese Optics Letters, 2016, 14(11): 111403 Copy Citation Text

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Abstract

In order to solve the problem of low measurement accuracy caused by uneven imaging resolutions, we develop a three-dimensional catadioptric vision sensor using 20 to 100 lasers arranged in a circular array called omnidirectional dot maxtric projection (ODMP). Based on the imaging characteristic of the sensor, the ODMP can image the area with a high image resolution. The proposed sensor with ODMP can minimize the loss of the detail information by adjusting the projection density. In evaluating the performance of the sensor, real experiments show the designed sensor has high efficiency and high precision for the measurement of the inner surfaces of pipelines.

θ = \tan^{- 1} (d / 2 f) .

(1)

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{\begin{matrix} z (t) = t \\ γ (t) = \sqrt{(e^{2} - 1) \cdot t^{2} + 2 p t - p^{2}} \end{matrix},

(2)

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{\begin{matrix} V_{i} (t) = [(m - ξ) - t, l - \sqrt{(e^{2} - 1) \cdot t^{2} + 2 p t - p^{2}}] \\ V_{r} (t) = [t + ξ, \sqrt{(e^{2} - 1) \cdot t^{2} + 2 p t - p^{2}}] \end{matrix} .

(3)

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r_{c} = \frac{\dot{S_{r}} {(t)}_{γ} V_{i} {(t)}_{z} - \dot{S_{r}} {(t)}_{z} V_{i} {(t)}_{γ}}{\dot{V_{i}} {(t)}_{z} V_{i} {(t)}_{γ} - \dot{V_{i}} {(t)}_{γ} V_{i} {(t)}_{z}},

(4)

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m = ξ + t - \frac{γ (t) (γ (t) - l) (ξ + t (3 - 2 e^{2}) - 2 p)}{e^{2} t (t (e^{2} - 1) + 2 p)} .

(5)

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Δ L = Δ L_{1} + Δ L_{2} = 2 f^{2} F δ L^{2} / f^{4} - F^{2} δ^{2} L^{2} .

(6)

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δ ϑ = δ A \cos^{3} (ψ) / f^{2} .

(7)

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δ S = δ A \cos (ψ) {(ξ + z (t))}^{2} / f^{2} \cos (ϕ),

(8)

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δ A / δ ω = f^{2} r_{c}^{2} (t) / [\cos (ψ) {(ξ + z (t))}^{2}] .

(9)

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p^{'} = [x y z]^{T} = [\begin{matrix} μ \end{matrix} ν \begin{matrix} S_{r} (ρ) \end{matrix}]^{T}, ρ = \sqrt{μ^{2} + ν^{2}},

(10)

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P^{'} = [X Y Z]^{T} = λ p^{'} = λ [μ ν \begin{matrix} S_{r} (ρ) \end{matrix}]^{T},

(11)

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{\begin{matrix} P^{'} = p R + T \\ P^{' T} V_{r} = P^{T} V_{r} \end{matrix},

(12)

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A x + B y + C z + D = 0,

(13)

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π^{T} P = 0, P^{T} V_{r} = 0 .

(14)

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Fuqiang Zhou, Xin Chen, Haishu Tan, Xinghua Chai. Three-dimensional catadioptric vision sensor using omnidirectional dot matrix projection[J]. Chinese Optics Letters, 2016, 14(11): 111403

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