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Christian Dornhege Publications
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2009
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Marc Gissler, Christian Dornhege, Bernhard Nebel and Matthias Teschner.
Deformable Proximity Queries and their Application in Mobile Manipulation Planning.
In
Symposium on Visual Computing (ISVC 2009).
2009.
To appear.
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Alexander Kleiner and Christian Dornhege.
Operator-Assistive Mapping in Harsh Environments.
In
Proceedings of the IEEE International Workshop on Safety, Security and Rescue Robotics
(SSRR 2009).
2009.
To appear.
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Teleoperation is a difficult task, particularly when
controlling robots from an isolated operator station.
In general, the operator has to solve nearly blindly the problems of mission
planning, target identification, robot navigation, and robot control at the same time.
The goal of the proposed system is to support teleoperated navigation
with real-time mapping.
We present a novel scan matching technique that re-considers data
associations during the search, enabling robust pose estimation even under
varying roll and pitch angle of the robot enabling mapping
on rough terrain.
The approach has been implemented as an embedded system and extensively tested
on robot platforms designed for teleoperation in critical situations, such as bomb
disposal.
Furthermore,
the system has been evaluated in a test maze by first responders during
the Disaster City event in Texas 2008.
Finally, experiments conducted within different environments show that
the system yields comparably accurate maps in real-time when
compared to higher sophisticated offline methods, such as Rao-Blackwellized SLAM.
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Christian Dornhege, Marc Gissler, Matthias Teschner and Bernhard Nebel.
Integrating Symbolic and Geometric Planning for Mobile Manipulation.
In
Proceedings of the IEEE International Workshop on Safety, Security and Rescue Robotics
(SSRR 2009).
2009.
To appear.
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Mobile manipulation requires to solve multiple subproblems.
One is planning in high-dimensional configuration spaces, that we approach in this work.
We decompose the manipulation problem into a symbolic and a geometric part.
The symbolic part is implemented as a classical symbolic planner that
tightly integrates a geometric planner enabling us to efficiently generate correct
plans.
A probabilistic roadmap planner constitutes the geometric part.
During the computation of the roadmap we utilize proximity queries to determine non-colliding configurations and to verify collision-free paths between configurations accurately and efficiently.
We demonstrate experiments in two scenarios, one of these being the manipulator dexterity test scenario that was
used in NIST's response robot evaluation in Disaster City.
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Christian Dornhege, Patrick Eyerich, Thomas Keller, Sebastian Trüg, Michael Brenner and Bernhard Nebel.
Semantic Attachments for Domain-Independent Planning Systems.
In
Proceedings of the 19th International Conference on Automated
Planning and Scheduling (ICAPS 2009), pp. 114-121.
AAAI Press 2009.
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Solving real-world problems using symbolic planning often
requires a simplified formulation of the original problem,
since certain subproblems cannot be represented at all or only
in a way leading to inefficiency. For example, manipulation
planning may appear as a subproblem in a robotic planning
context or a packing problem can be part of a logistics
task. In this paper we propose an extension of PDDL for
specifying semantic attachments. This allows the evaluation of
grounded predicates as well as the change of fluents by
externally specified functions. Furthermore, we describe a
general schema of integrating semantic attachments into a
forward-chaining planner and report on our experience of
adding this extension to the planners FF and Temporal Fast
Downward. Finally, we present some preliminary experiments
using semantic attachments.
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Moritz Göbelbecker and Christian Dornhege.
Realistic Cities in Simulated Environments - An Open Street Map to Robocup Rescue Converter.
In
Online-Proceedings of the Fourth International Workshop on Synthetic Simulation
and Robotics to Mitigate Earthquake Disaster (SRMED 2009).
2009.
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A general problem when developing large scale disaster simulation environments is to acquire GIS data.
In this work, we tackle the problem of map generation from public sources.
Usually the major problem is not only the data conversion itself, but to get access to the data at all.
We solve this problem by using the website OpenStreetMap.org, that provides mapping data for the whole world in a wiki-style concept, as our source of data,
thus being able to generate maps for almost any city.
The data is converted to the format required by the Robocup Rescue Simulation System, enabling simulations
on various real-world scenarios.
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Rainer Kümmere, Bastian Steder, Christian Dornhege, Michael Ruhnke, Giorgio Grisetti, Cyrill Stachniss and Alexander Kleiner.
On measuring the accuracy of SLAM algorithms.
Autonomous Robots 27 (4), pp. 387-407. 2009.
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In this paper, we address the problem of creating an objective benchmark for evaluating SLAM approaches. We propose a framework for analyzing the results of a SLAM approach based on a metric for measuring the error of the corrected trajectory. This metric uses only relative relations between poses and does not rely on a global reference frame. This overcomes serious shortcomings of approaches using a global reference frame to compute the error. Our method furthermore allows us to compare SLAM approaches that use different estimation techniques or different sensor modalities since all computations are made based on the corrected trajectory of the robot.
We provide sets of relative relations needed to compute our metric for an extensive set of datasets frequently used in the robotics community. The relations have been obtained by manually matching laser-range observations to avoid the errors caused by matching algorithms. Our benchmark framework allows the user to easily analyze and objectively compare different SLAM approaches.
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Wolfram Burgard, Cyrill Stachniss, Giorgio Grisetti, Bastian Steder, Rainer Kümmerle, Christian Dornhege, Michael Ruhnke, Alexander Kleiner and Juan D. Tardos.
A Comparison of SLAM Algorithms Based on a Graph of Relations.
In
Proceedings of the IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS).
2009.
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In this paper, we address the problem of creating
an objective benchmark for comparing SLAM approaches.
We propose a framework for analyzing the results of SLAM
approaches based on a metric for measuring the error of the
corrected trajectory. The metric uses only relative relations
between poses and does not rely on a global reference frame.
The idea is related to graph-based SLAM approaches in
the sense that it considers the energy needed to deform the
trajectory estimated by a SLAM approach to the ground
truth trajectory. Our method enables us to compare SLAM
approaches that use different estimation techniques or different
sensor modalities since all computations are made based on the
corrected trajectory of the robot. We provide sets of relative
relations needed to compute our metric for an extensive set
of datasets frequently used in the SLAM community. The
relations have been obtained by manually matching laser-range
observations. We believe that our benchmarking framework
allows the user an easy analysis and objective comparisons
between different SLAM approaches.
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Rainer Kümmerle, Bastian Steder, Christian Dornhege, Alexander Kleiner, Giorgio Grisetti and Wolfram Burgard.
Large Scale Graph-based SLAM using Aerial Images as Prior Information.
In
Proceedings of Robotics: Science and Systems (RSS).
2009.
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To effectively navigate in their environments and accurately reach their target locations, mobile robots require a globally consistent map of the environment. The problem of learning a map with a mobile robot has been intensively studied in the past and is usually referred to as the simultaneous localization and mapping (SLAM) problem. However, existing solutions to the SLAM problem typically rely on loop-closures to obtain global consistency and do not exploit prior information even if it is available. In this paper, we present a novel SLAM approach that achieves global consistency by utilizing publicly accessible aerial photographs as prior information. Our approach inserts correspondences found between three-dimensional laser range scans and the aerial image as constraints into a graph-based formulation of the SLAM problem. We evaluate our algorithm based on large real-world datasets acquired in a mixed in- and outdoor environment by comparing the global accuracy with state-of-the-art SLAM approaches and GPS. The experimental results demonstrate that the maps acquired with our method show increased global consistency.
2007
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Alexander Kleiner and Christian Dornhege.
Real-time Localization and Elevation Mapping within Urban Search and Rescue Scenarios.
Journal of Field Robotics 24, pp. 723-745. 2007.
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Alexander Kleiner, Christian Dornhege and Dali Sun.
Mapping disaster areas jointly: RFID-Coordinated SLAM by Humans and Robots.
In
Proceedings of the IEEE International Workshop on Safety, Security
and Rescue Robotics (SSRR 2007).
Rome, Italy 2007.
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Christian Dornhege and Alexander Kleiner.
Behavior maps for online planning of obstacle negotiation and climbing on rough terrain.
In
Proceedings of the IEEE/RSJ International Conference on Intelligent
Robots and Systems (IROS 2007).
San Diego, California 2007.
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Christian Dornhege and Alexander Kleiner.
Behavior maps for online planning of obstacle negotiation and climbing on rough terrain.
In
Video Proceedings of the IEEE/RSJ International Conference on Intelligent
Robots and Systems (IROS 2007).
San Diego, California 2007.
2006
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Christian Dornhege and Alexander Kleiner.
Visual Odometry for Tracked Vehicles.
In
Proceedings of the IEEE International Workshop on Safety, Security and Rescue Robotics (SSRR 2006).
Gaithersburg, USA 2006.
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Alexander Kleiner, Christian Dornhege, Rainer Kuemmerle, Michael Ruhnke, Bastian Steder, Bernhard Nebel, Patrick Doherty, Mariusz Wzorek, Piotr Rudol, Gianpaolo Conte, S. Durante and D. Lundstrom.
RoboCupRescue - Simulation League Team RescueRobots Freiburg (Germany), Team Description Paper.
In
CDROM Proceedings of the International RoboCup Symposium '05.
Bremen, Germany 2006.
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This paper describes the approach of the RescueRobots Freiburg team,
which is a team of students from the University of Freiburg that originates from
the former CS Freiburg team (RoboCupSoccer) and the ResQ Freiburg team
(RoboCupRescue Simulation). Furthermore we introduce linkMAV, a micro aerial
vehicle platform.
Our approach covers RFID-based SLAM and exploration, autonomous detection
of relevant 3D structures, visual odometry, and autonomous victim identification.
Furthermore, we introduce a custom made 3D Laser Range Finder (LRF) and a
novel mechanism for the active distribution of RFID tags.
2005
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Alexander Kleiner, Michael Brenner, Tobias Braeuer, Christian Dornhege, Moritz Göbelbecker, Matthias Luber, Johann Prediger, Joerg Stueckler and Bernhard Nebel.
Successful Search and Rescue in Simulated Disaster Areas.
In
Proceedings of the International RoboCup Symposium '05.
Osaka, Japan 2005.
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RoboCupRescue Simulation is a large-scale multi-agent simulation
of urban disasters where, in order to save lives and minimize damage, rescue
teams must effectively cooperate despite sensing and communication limitations.
This paper presents the comprehensive search and rescue approach of the ResQ
Freiburg team, the winner in the RoboCupRescue Simulation league at RoboCup
2004.
Specific contributions include the predictions of travel costs and civilian lifetime,
the efficient coordination of an active disaster space exploration, as well as
an any-time rescue sequence optimization based on a genetic algorithm.
We compare the performances of our team and others in terms of their capability
of extinguishing fires, freeing roads from debris, disaster space exploration, and
civilian rescue. The evaluation is carried out with information extracted from
simulation log files gathered during RoboCup 2004. Our results clearly explain
the success of our team, and also confirm the scientific approaches proposed in
this paper.
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Alexander Kleiner, Bastian Steder, Christian Dornhege, Daniel Hoefler, Daniel Meyer-Delius, Johann Prediger, Joerg Stueckler, Kolja Glogowski, Markus Thurner, Matthias Luber, Michael Schnell, Rainer Kuemmerle, Timothy Burk, Tobias Braeuer and Bernhard Nebel.
RoboCupRescue - Robot League Team RescueRobots Freiburg (Germany), Team Description Paper.
In
CDROM Proceedings of the International RoboCup Symposium '05.
Osaka, Japan 2005.
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This paper describes the approach of the RescueRobots Freiburg team.
RescueRobots Freiburg is a team of students from the university of Freiburg, that
originates from the former CS Freiburg team (RoboCupSoccer) and the ResQ
Freiburg team (RoboCupRescue Simulation).
Due to the high versatility of the RoboCupRescue competition we tackle the three
arenas by a a twofold approach: On the one hand we want to introduce robust
vehicles that can safely be teleoperated through rubble and building debris while
constructing three-dimensional maps of the environment. On the other hand we
want to introduce a team of autonomous robots that quickly explore a large terrain
while building a two-dimensional map. This two solutions are particularly wellsuited
for the red and yellow arena, respectively. Our solution for the orange arena
will finally be decided between these two, depending on the capabilities of both
approaches at the venue.
In this paper, we introduce some preliminary results that we achieved so far from
map building, localization, and autonomous victim identification. Furthermore
we introduce a custom made 3D Laser Range Finder (LRF) and a novel mechanism
for the active distribution of RFID tags.
1 Introduction
RescueRobots Freiburg is a team of students from the university of Freiburg. The team
originates from the former CS Freiburg team[6], which won three times the RoboCup
world championship in the RoboCupSoccer F2000 league, and the ResQ Freiburg team[2],
which won the last RoboCup world championship in the RoboCupRescue Simulation
league. The team approach proposed in this paper is based on experiences gathered at
RoboCup during the last six years.
Due to the high versatility of the RoboCupRescue competition we tackle the three
arenas by a twofold approach: On the one hand we want to introduce a vehicle that
can safely be teleoperated through rubble and building debris while constructing threedimensional
maps of the environment. On the other hand we want to introduce an autonomous
team of robots that quickly explore a large terrain while building a twodimensional
map. This two solutions are particularly well-suited for the red and yellow
arena, respectively. Our solution for the orange arena will finally be decided between
these two, depending on the capabilities of both approaches at the venue.
2004
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