29 research outputs found
Trajectory Optimization and Following for a Three Degrees of Freedom Overactuated Floating Platform
Space robotics applications, such as Active Space Debris Removal (ASDR),
require representative testing before launch. A commonly used approach to
emulate the microgravity environment in space is air-bearing based platforms on
flat-floors, such as the European Space Agency's Orbital Robotics and GNC Lab
(ORGL). This work proposes a control architecture for a floating platform at
the ORGL, equipped with eight solenoid-valve-based thrusters and one reaction
wheel. The control architecture consists of two main components: a trajectory
planner that finds optimal trajectories connecting two states and a trajectory
follower that follows any physically feasible trajectory. The controller is
first evaluated within an introduced simulation, achieving a 100 % success rate
at finding and following trajectories to the origin within a Monte-Carlo test.
Individual trajectories are also successfully followed by the physical system.
In this work, we showcase the ability of the controller to reject disturbances
and follow a straight-line trajectory within tens of centimeters.Comment: Accepted to IROS2022, code at
https://gitlab.com/anton.bredenbeck/ff-trajectorie
A Study of Projections for Key Point Based Registration of Panoramic Terrestrial 3D Laser Scans
Abstract This paper surveys state of the art image features and descriptors for the task of 3D scan registration based on panoramic reflectance images. As modern terrestrial laser scanners digitize their environment in a spherical way, the sphere has to be projected to a two-dimensional image. To this end, we evaluate the equirectangular, the cylindrical, the Mercator, the rectilinear, the Pannini, the stereographic, and the z-axis projection. We show that the Mercator and the Pannini projection outperform the other projection methods
Finding and Following Optimal Trajectories for an Overactuated Floating Robotic Platform
The recent increase in yearly spacecraft launches and the high number of
planned launches have raised questions about maintaining accessibility to space
for all interested parties. A key to sustaining the future of space-flight is
the ability to service malfunctioning - and actively remove dysfunctional
spacecraft from orbit. Robotic platforms that autonomously perform these tasks
are a topic of ongoing research and thus must undergo thorough testing before
launch. For representative system-level testing, the European Space Agency
(ESA) uses, among other things, the Orbital Robotics and GNC Lab (ORGL), a
flat-floor facility where air-bearing based platforms exhibit free-floating
behavior in three Degrees of Freedom (DoF). This work introduces a
representative simulation of a free-floating platform in the testing
environment and a software framework for controller development. Finally, this
work proposes a controller within that framework for finding and following
optimal trajectories between arbitrary states, which is evaluated in simulation
and reality.Comment: 16th Symposium on Advanced Space Technologies in Robotics and
Automation 202
Unconventional Trajectories for Mobile 3D Scanning and Mapping
State-of-the-art LiDAR-based 3D scanning and mapping systems focus on scenarios where good sensing coverage is ensured, such as drones, wheeled robots, cars, or backpack-mounted systems. However, in some scenarios more unconventional sensor trajectories come naturally, e.g., rolling, descending, or oscillating back and forth, but the literature on these is relatively sparse. As a result, most implementations developed in the past are not able to solve the SLAM problem in such conditions. In this chapter, we propose a robust offline-batch SLAM system that is able to address more challenging trajectories, which are characterized by weak angles of incidence and limited FOV while scanning. The proposed SLAM system is an upgraded version of our previous work and takes as input the raw points and prior pose estimates, yet the latter are subject to large amounts of drift. Our approach is a two-staged algorithm where in the first stage coarse alignment is fast achieved by matching planar polygons. In the second stage, we utilize a graph-based SLAM algorithm for further refinement. We evaluate the mapping accuracy of the algorithm on our own recorded datasets using high-resolution ground truth maps, which are available from a TLS
A sensor skid for precise 3d modeling of production lines
ABSTRACT: Motivated by the increasing need of rapid characterization of environments in 3D, we designed and built a sensor skid that automates the work of an operator of terrestrial laser scanners. The system combines terrestrial laser scanning with kinematic laser scanning and uses a novel semi-rigid SLAM method. It enables us to digitize factory environments without the need to stop production. The acquired 3D point clouds are precise and suitable to detect objects that collide with items moved along the production line
Multi-modale 3D-Kartierung - Kombination von 3D-Punktwolken mit Thermo- und Farbinformation
Imagine a technology that automatically creates a full 3D thermal model of an environment and detects temperature peaks in it. For better orientation in the model it is enhanced with color information. The current state of the art for analyzing temperature related issues is thermal imaging. It is relevant for energy efficiency but also for securing important infrastructure such as power supplies and temperature regulation systems. Monitoring and analysis of the data for a large building is tedious as stable conditions need to be guaranteed for several hours and detailed notes about the pose and the environment conditions for each image must be taken. For some applications repeated measurements are necessary to monitor changes over time. The analysis of the scene is only possible through expertise and experience.
This thesis proposes a robotic system that creates a full 3D model of the environment with color and thermal information by combining thermal imaging with the technology of terrestrial laser scanning. The addition of a color camera facilitates the interpretation of the data and allows for other application areas. The data from all sensors collected at different positions is joined in one common reference frame using calibration and scan matching. The first part of the thesis deals with 3D point cloud processing with the emphasis on accessing point cloud data efficiently, detecting planar structures in the data and registering multiple point clouds into one common coordinate system. The second part covers the autonomous exploration and data acquisition with a mobile robot with the objective to minimize the unseen area in 3D space. Furthermore, the combination of different modalities, color images, thermal images and point cloud data through calibration is elaborated. The last part presents applications for the the collected data. Among these are methods to detect the structure of building interiors for reconstruction purposes and subsequent detection and classification of windows. A system to project the gathered thermal information back into the scene is presented as well as methods to improve the color information and to join separately acquired point clouds and photo series.
A full multi-modal 3D model contains all the relevant geometric information about the recorded scene and enables an expert to fully analyze it off-site. The technology clears the path for automatically detecting points of interest thereby helping the expert to analyze the heat flow as well as localize and identify heat leaks. The concept is modular and neither limited to achieving energy efficiency nor restricted to the use in combination with a mobile platform. It also finds its application in fields such as archaeology and geology and can be extended by further sensors.Man stelle sich eine Technologie vor, die automatisch ein vollständiges
3D-Thermographiemodell einer Umgebung generiert und Temperaturspitzen darin
erkennt. Zur besseren Orientierung innerhalb des Modells ist dieses mit
Farbinformationen erweitert. In der Analyse temperaturrelevanter Fragestellungen
sind Thermalbilder der Stand der Technik. Darunter fallen Energieeffizienz und
die Sicherung wichtiger Infrastruktur, wie Energieversorgung und Systeme zur
Temperaturregulierung. Die Überwachung und anschließende Analyse der Daten eines
großen Gebäudes ist aufwändig, da über mehrere Stunden stabile Bedingungen
garantiert und detaillierte Aufzeichnungen über die Aufnahmeposen und die
Umgebungsverhältnisse für jedes Wärmebild erstellt werden müssen. Einige
Anwendungen erfordern wiederholte Messungen, um Veränderungen über die Zeit zu
beobachten. Eine Analyse der Szene ist nur mit Erfahrung und Expertise möglich.
Diese Arbeit stellt ein Robotersystem vor, das durch Kombination von
Thermographie mit terrestrischem Laserscanning ein vollständiges 3D Modell der
Umgebung mit Farb- und Temperaturinformationen erstellt. Die ergänzende
Farbkamera vereinfacht die Interpretation der Daten und eröffnet weitere
Anwendungsfelder. Die an unterschiedlichen Positionen aufgenommenen Daten aller
Sensoren werden durch Kalibrierung und Scanmatching in einem gemeinsamen
Bezugssystem zusammengefügt. Der erste Teil der Arbeit behandelt
3D-Punktwolkenverarbeitung mit Schwerpunkt auf effizientem Punktzugriff,
Erkennung planarer Strukturen und Registrierung mehrerer Punktwolken in einem
gemeinsamen Koordinatensystem. Der zweite Teil beschreibt die autonome Erkundung
und Datenakquise mit einem mobilen Roboter, mit dem Ziel, die bisher nicht
erfassten Bereiche im 3D-Raum zu minimieren. Des Weiteren wird die Kombination
verschiedener Modalitäten, Farbbilder, Thermalbilder und Punktwolken durch
Kalibrierung ausgearbeitet. Den abschließenden Teil stellen Anwendungsszenarien
für die gesammelten Daten dar, darunter Methoden zur Erkennung der
Innenraumstruktur für die Rekonstruktion von Gebäuden und der anschließenden
Erkennung und Klassifizierung von Fenstern. Ein System zur Rückprojektion der
gesammelten Thermalinformation in die Umgebung wird ebenso vorgestellt wie
Methoden zur Verbesserung der Farbinformationen und zum Zusammenfügen separat
aufgenommener Punktwolken und Fotoreihen.
Ein vollständiges multi-modales 3D Modell enthält alle relevanten geometrischen
Informationen der aufgenommenen Szene und ermöglicht einem Experten, diese
standortunabhängig zu analysieren. Diese Technologie ebnet den Weg für die
automatische Erkennung relevanter Bereiche und für die Analyse des Wärmeflusses
und vereinfacht somit die Lokalisierung und Identifikation von Wärmelecks für
den Experten. Das vorgestellte modulare Konzept ist weder auf den Anwendungsfall
Energieeffizienz beschränkt noch auf die Verwendung einer mobilen Plattform
angewiesen. Es ist beispielsweise auch in Feldern wie der Archäologie und
Geologie einsetzbar und kann durch zusätzliche Sensoren erweitert werden
Algorithmic Solutions for Computing Precise Maximum Likelihood 3D Point Clouds from Mobile Laser Scanning Platforms
Mobile laser scanning puts high requirements on the accuracy of the positioning systems and the calibration of the measurement system. We present a novel algorithmic approach for calibration with the goal of improving the measurement accuracy of mobile laser scanners. We describe a general framework for calibrating mobile sensor platforms that estimates all configuration parameters for any arrangement of positioning sensors, including odometry. In addition, we present a novel semi-rigid Simultaneous Localization and Mapping (SLAM) algorithm that corrects the vehicle position at every point in time along its trajectory, while simultaneously improving the quality and precision of the entire acquired point cloud. Using this algorithm, the temporary failure of accurate external positioning systems or the lack thereof can be compensated for. We demonstrate the capabilities of the two newly proposed algorithms on a wide variety of datasets
Indoor 3D LIDAR scans with thermal images for mapping (the Automation Lab at Jacobs University Bremen)
This data set was recorded using a Riegl VZ-400 and a Optris PI IR camera. It contains several 3D scans taken around the Automation Lab at Jacobs University Bremen. The data set consists of scans and thermal images taken at different poses