A novel encoding element for robust pose estimation using planar fiducials.

Pose estimation in robotics is often achieved using images from known and purposefully applied markers or fiducials taken by a monocular camera. This low-cost system architecture can provide accurate and precise pose estimation measurements. However, to prevent the restriction of robotic movement and occlusions of features, the fiducial markers are often planar. While numerous planar fiducials exist, the performance of these markers suffers from pose ambiguities and loss of precision under frontal observations. These issues are most prevalent in systems with less-than-ideal specifications such as low-resolution detectors, low field of view optics, far-range measurements etc. To mitigate these issues, encoding markers have been proposed in literature. These markers encode an extra dimension of information in the signal between marker and sensor, thus increasing the robustness of the pose solution. In this work, we provide a survey of these encoding markers and show that existing solutions are complex, require optical elements and are not scalable. Therefore, we present a novel encoding element based on the compound eye of insects such as the Mantis. The encoding element encodes a virtual point in space in its signal without the use of optical elements. The features provided by the encoding element are mathematically equivalent to those of a protrusion. Where existing encoding fiducials require custom software, the projected virtual point can be used with standard pose solving algorithms. The encoding element is simple, can be produced using a consumer 3D printer and is fully scalable. The end-to-end implementation of the encoding element proposed in this work significantly increases the pose estimation performance of existing planar fiducials, enabling robust pose estimation for robotic systems.

Design trade-off and proof of concept for LOUPE, the Lunar Observatory for Unresolved Polarimetry of Earth.

We provide a proof of the technical feasibility of LOUPE, the first integral-field snapshot spectropolarimeter, designed to monitor the reflected flux and polarization spectrum of Earth. These are to be used as benchmark data for the retrieval of biomarkers and atmospheric and surface characteristics from future direct observations of exoplanets. We perform a design trade-off for an implementation in which LOUPE performs snapshot integral-field spectropolarimetry at visible wavelengths. We used off-the-shelf optics to construct a polarization modulator, in which polarization information is encoded into the spectrum as a wavelength-dependent modulation, while spatial resolution is maintained using a micro-lens array. The performance of this design concept is validated in a laboratory setup. Our proof-of-concept is capable of measuring a grid of 50 × 50 polarization spectra between 610 and 780 nm of a mock target planet - proving the merit of this design. The measurements are affected by systematic noise on the percent level, and we discuss how to mitigate this in future iterations. We conclude that LOUPE can be small and robust while meeting the science goals of this particular space application, and note the many potential applications that may benefit from our concept for doing snapshot integral-field spectropolarimetry.