| 1. |
- Kleiner, Alexander, et al.
(författare)
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ARMO - Adaptive Road Map Optimization for Large Robot Teams
- 2011
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Ingår i: IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS). - : IEEE conference proceedings. ; , s. 3276-3282
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Konferensbidrag (refereegranskat)abstract
- Autonomous robot teams that simultaneously dispatch transportation tasks are playing more and more an important role in present logistic centers and manufacturing plants. In this paper we consider the problem of robot motion planning for large robot teams in the industrial domain. We present adaptive road map optimization (ARMO) that is capable of adapting the road map in real time whenever the environment has changed. Based on linear programming, ARMO computes an optimal road map according to current environmental constraints (including human whereabouts) and the current demand for transportation tasks from loading stations in the plant. For detecting dynamic changes, the environment is describe by a grid map augmented with a hidden Markov model (HMM). We show experimentally that ARMO outperforms decoupled planning in terms of computation time and time needed for task completion.
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| 2. |
- Kleiner, Alexander, et al.
(författare)
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RoboCupRescue - Robot League Team RescueRobots Freiburg (Germany)
- 2005
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Ingår i: RoboCup 2005 (CDROM Proceedings), Team Description Paper, Rescue Robot League.
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Konferensbidrag (refereegranskat)abstract
- 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 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. 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.
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| 3. |
- Meyer-Delius, D., et al.
(författare)
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Using artificial landmarks to reduce the ambiguity in the environment of a mobile robot
- 2011
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Ingår i: IEEE Int. Conf. on Robotics and Automation (ICRA). ; , s. 5173-5178
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Konferensbidrag (refereegranskat)abstract
- Robust and reliable localization is a fundamental prerequisite for many applications of mobile robots. Although there exist many solutions to the localization problem, structurally symmetrical or featureless environments can prevent different locations from being distinguishable given the data obtained with the robot’s sensors. Such ambiguities typically make localization approaches more likely to fail. In this paper, we investigate how artificial landmarks can be utilized to reduce the ambiguity in the environment. We present a practical approach to compute a configuration of indistinguishable landmarks that decreases the overall ambiguity and thus increases the robustness of the localization process. We evaluate our approach in different environments based on real data and in simulation. Our results demonstrate that our approach improves the localization performance of the robot and outperforms other landmark selection approaches.
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