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An environmental camera is a camera embedded in a working environment to provide vision guidance to a mobile robot.
In the setup of such robot systems, the relative position and orientation between the mobile robot and the environmental camera are parameters that must unavoidably be calibrated.
The simulation and error analysis presented here will be useful for designing an environmental camera that can elucidate the dust and water vapor properties in a future Mars lander mission.
We have developed a method to retrieve optical and physical properties of Martian dust from spectral intensities of direct and scattered solar radiation to be measured using a multi-wavelength environmental camera onboard a Mars lander.
We have constructed a Martian dust model in order to retrieve optical/physical properties of Martian dust from DSR/SSR spectra to be measured by a multi-wavelength environmental camera onboard a Mars lander.
In this paper, a method is proposed for the robot system in which calibration of the environmental camera is rendered by the robot system itself on the spot after a system is set up. Specific kinds of motion patterns of the mobile robot, which are called test motions, have been explored for calibration.
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Water vapor absorption bands are located inside the sensitive range (350 1000 nm) of conventional complementary metal-oxide semiconductor (CMOS) sensors to be employed for our environmental monitor camera.
Spectral irradiance/radiance of DSR/SSR in the visible and near infrared spectral regions is to be measured with an environmental monitor camera onboard a Mars lander.
The visibility and contrast of the captured images may be affected and may be degraded by many reasons, such as poor environmental condition, camera sensor noise, and other uncertain factors [3, 4].
Data sources are around us everywhere, smart phones, computers, environmental sensors, cameras, GPS (Geographical Positioning Systems), and even people.
Infrared sensors are largely employed in lane marking detection without the environmental limitations of cameras and lighting.
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