Evaluation of 3D CNN Semantic Mapping for Rover Navigation

Terrain assessment is a key aspect for autonomous exploration rovers, surrounding environment recognition is required for multiple purposes, such as optimal trajectory planning and autonomous target identification. In this work we present a technique to generate accurate three-dimensional semantic maps for Martian environment. The algorithm uses as input a stereo image acquired by a camera mounted on a rover. Firstly, images are labeled with DeepLabv3+, which is an encoder-decoder Convolutional Neural Networl (CNN). Then, the labels obtained by the semantic segmentation are combined to stereo depth-maps in a Voxel representation. We evaluate our approach on the ESA Katwijk Beach Planetary Rover Dataset.Comment: To be presented at the 7th IEEE International Workshop on Metrology for Aerospace (MetroAerospace

Metrological characterization of a vision-based system for relative pose measurements with fiducial marker mapping for spacecrafts

An improved approach for the measurement of the relative pose between a target and a chaser spacecraft is presented. The selected method is based on a single camera, which can be mounted on the chaser, and a plurality of fiducial markers, which can be mounted on the external surface of the target. The measurement procedure comprises of a closed-form solution of the Perspective from n Points (PnP) problem, a RANdom SAmple Consensus (RANSAC) procedure, a non-linear local optimization and a global Bundle Adjustment refinement of the marker map and relative poses. A metrological characterization of the measurement system is performed using an experimental set-up that can impose rotations combined with a linear translation and can measure them. The rotation and position measurement errors are calculated with reference instrumentations and their uncertainties are evaluated by the Monte Carlo method. The experimental laboratory tests highlight the significant improvements provided by the Bundle Adjustment refinement. Moreover, a set of possible influencing physical parameters are defined and their correlations with the rotation and position errors and uncertainties are analyzed. Using both numerical quantitative correlation coefficients and qualitative graphical representations, the most significant parameters for the final measurement errors and uncertainties are determined. The obtained results give clear indications and advice for the design of future measurement systems and for the selection of the marker positioning on a satellite surface

Simulation Framework for Mobile Robots in Planetary-Like Environments

In this paper we present a simulation framework for the evaluation of the navigation and localization metrological performances of a robotic platform. The simulator, based on ROS (Robot Operating System) Gazebo, is targeted to a planetary-like research vehicle which allows to test various perception and navigation approaches for specific environment conditions. The possibility of simulating arbitrary sensor setups comprising cameras, LiDARs (Light Detection and Ranging) and IMUs makes Gazebo an excellent resource for rapid prototyping. In this work we evaluate a variety of open-source visual and LiDAR SLAM (Simultaneous Localization and Mapping) algorithms in a simulated Martian environment. Datasets are captured by driving the rover and recording sensors outputs as well as the ground truth for a precise performance evaluation.Comment: To be presented at the 7th IEEE International Workshop on Metrology for Aerospace (MetroAerospace

Structural analysis of grabens, Pit Chains and rifting in Noctis Labyrinthus (Mars) based on data derived from HRSC and MOLA.

ResearchAims: 1. Study the tectonic features and the stress field in NoctisLabyrinthus. 2. Scrutinize the PitChainsmorohologyand evolution. 3. Reveal the processes responsible for the complex ramify rift systems and troug

Uncertainty analysis of image features for vision applications in space

A detailed uncertainty analysis for the position of image features is described. Three main uncertainty sources are identified and evaluated: image noise, lighting direction and image resolution. Since the proposed method does not need to acquire multiple images of the same scene in the same shooting conditions, it is particularly suited for applications with a relative motion between the camera and the scene and/or between the lighting source and the scene. The described method is applied to the images acquired during the recent asteroid Lutetia fly-by using the Narrow Angle Camera of the OSIRIS instrument. OSIRIS is a payload of the Rosetta ESA space mission. The obtained numerical results, including histograms and standard uncertainties, are depicted and discussed

Occupancy grid mapping for rover navigation based on semantic segmentation

Obstacle mapping is a fundamental building block of the autonomous navigation pipeline of many robotic platforms such as planetary rovers. Nowadays, occupancy grid mapping is a widely used tool for obstacle perception. It foreseen the representation of the environment in evenly spaced cells, whose posterior probability of being occupied is updated based on range sensors measurement. In more classic approaches, the cells are updated to occupied at the point where the ray emitted by the range sensor encounters an obstacle, such as a wall. The main limitation of this kind of methods is that they are not able to identify planar obstacles, such as slippery, sandy, or rocky soils. In this work, we use the measurements of a stereo camera combined with a pixel labeling technique based on Convolution Neural Networks to identify the presence of rocky obstacles in planetary environment. Once identified, the obstacles are converted into a scan-like model. The estimation of the relative pose between successive frames is carried out using ORB-SLAM algorithm. The final step consists of updating the occupancy grid map using the Bayes' update Rule. To evaluate the metrological performances of the proposed method images from the Martian analogous dataset, the ESA Katwijk Beach Planetary Rover Dataset have been used. The evaluation has been performed by comparing the generated occupancy map with a manually segmented ortomosaic map, obtained by drones' survey of the area used as reference

Observing Mercury: from Galileo to the stereo camera on the BepiColombo mission

AbstractAfter having observed the planets from his house in Padova using his telescope, in January 1611 Galileo wrote to Giuliano de Medici that Venus is moving around the Sun as Mercury. Forty years ago, Giuseppe Colombo, professor of Celestial Mechanics in Padova, made a decisive step to clarify the rotational period of Mercury. Today, scientists and engineers of the Astronomical Observatory of Padova and of the University of Padova, reunited in the Center for Space Studies and Activities (CISAS) named after Giuseppe Colombo, are busy to realize a stereo camera (STC) that will be on board the European (ESA) and Japanese (JAXA) space mission BepiColombo, devoted to the observation and exploration of the innermost planet. This paper will describe the stereo camera, which is one of the channels of the SIMBIOSYS instrument, aiming to produce the global mapping of the surface with 3D images

In-lab characterization of HYPSOS, a novel stereo hyperspectral observing system: first results

HYPSOS (HYPerspectral Stereo Observing System, patented) is a novel remote sensing instrument able to extract the spectral information from the two channels of a pushbroom stereo camera; thus it simultaneously provides 4D information, spatial and spectral, of the observed features. HYPSOS has been designed to be a compact instrument, compatible with small satellite applications, to be suitable both for planetary exploration as well for terrestrial environmental monitoring. An instrument with such global capabilities, both in terms of scientific return and needed resources, is optimal for fully characterizing the observed surface of investigation. HYPSOS optical design couples a pair of folding mirrors to a modified three mirror anastigmat telescope for collecting the light beams from the optical paths of the two stereo channels; then, on the telescope focal plane, there is the entrance slit of an imaging spectrograph, which selects and disperses the light from the two stereo channels on a bidimensional detector. With this optical design, the two stereo channels share the large majority of the optical elements: this allowed to realize a very compact instrument, which needs much less resources than an equivalent system composed by a stereo camera and a spectrometer. To check HYPSOS actual performance, we realized an instrument prototype to be operated in a laboratory environment. The laboratory setup is representative of a possible flight configuration: the light diffused by a surface target is collimated on the HYPSOS channel entrance apertures, and the target is moved with respect to the instrument to reproduce the in- flight pushbroom acquisition mode. Here we describe HYPSOS and the ground support equipment used to characterize the instrument, and show the preliminary results of the instrument alignment activities