PhD Thesis Poppinga: RRT - Jacobs University
PhD Thesis Poppinga: RRT - Jacobs University
PhD Thesis Poppinga: RRT - Jacobs University
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• Jann <strong>Poppinga</strong>, Max Pfingsthorn, Soeren Schwertfeger, Kaustubh Pathak, and Andreas Birk.<br />
Optimized Octtree Datastructure and Access Methods for 3D Mapping. In IEEE Safety, Security,<br />
and Rescue Robotics (SSRR). IEEE Press, 2007,<br />
henceforth referred to as [<strong>Poppinga</strong> et al., 2007].<br />
The patch map datastructure is built based on the work by Kaustubh Pathak, published in:<br />
• Andreas Birk, Kaustubh Pathak, Narunas Vaskevicius, Max Pfingsthorn, Jann <strong>Poppinga</strong>, and<br />
Soeren Schwertfeger. Surface Representations for 3D Mapping: A Case for a Paradigm Shift.<br />
KI - German Journal on Artificial Intelligence, 2010.<br />
• Kaustubh Pathak, Andreas Birk, Narunas Vaskevicius, Max Pfingsthorn, Soeren Schwertfeger,<br />
and Jann <strong>Poppinga</strong>. Online 3D SLAM by Registration of Large Planar Surface Segments and<br />
Closed Form Pose-Graph Relaxation. Journal of Field Robotics, Special Issue on 3D Mapping,<br />
27(1):52–84, 2010.<br />
• Kaustubh Pathak, Narunas Vaskevicius, Jann <strong>Poppinga</strong>, Max Pfingsthorn, Soeren Schwertfeger,<br />
and Andreas Birk. Fast 3D Mapping by Matching Planes Extracted from Range Sensor Point-<br />
Clouds. In International Conference on Intelligent Robots and Systems (IROS). IEEE Press,<br />
2009.<br />
• Andreas Birk, Narunas Vaskevicius, Kaustubh Pathak, Soeren Schwertfeger, Jann <strong>Poppinga</strong>,<br />
and Heiko Buelow. 3-D Perception and Modeling: Motion-Level Teleoperation and Intelligent<br />
Autonomous Functions. IEEE Robotics and Automation Magazine (RAM), December, 2009.<br />
• K. Pathak, A. Birk, N. Vaškevičius, and J. <strong>Poppinga</strong>. Fast registration based on noisy planes<br />
with unknown correspondences for 3-d mapping. Robotics, IEEE Transactions on, 26(3):424<br />
–441, June 2010, henceforth referred to as [Pathak et al., 2010b].<br />
Data collected by me and library functions implemented by me were used in object classification:<br />
• Soeren Schwertfeger, Jann <strong>Poppinga</strong>, and Andreas Birk. Towards Object Classification using<br />
3D Sensor Data. In ECSIS Symposium on Learning and Adaptive Behaviors for Robotic Systems<br />
(LAB-RS). IEEE, 2008.<br />
In an unrelated educational project, I worked with humanoid robots:<br />
• Andreas Birk, Jann <strong>Poppinga</strong>, and Max Pfingsthorn. Using different Humanoid Robots for<br />
Science Edutainment of Secondary School Pupils. In Luca Iocchi, Hitoshi Matsubara, Alfredo<br />
Weitzenfeld, and Changjiu Zhou, editors, RoboCup 2008: Robot WorldCup XII, Lecture Notes<br />
in Artificial Intelligence (LNAI). Springer, 2009.<br />
Based on my work with the SwissRanger sensor, K. Pathak implemented a forward sensor model,<br />
sensor fusion, and achieved sub-pixel accuracy:<br />
6<br />
• Kaustubh Pathak, Andreas Birk, Soeren Schwertfeger, and Jann <strong>Poppinga</strong>. 3D Forward Sensor<br />
Modeling and Application to Occupancy Grid Based Sensor Fusion. In International Conference<br />
on Intelligent Robots and Systems (IROS), pages 2059 – 2064, San Diego, USA, 2007.<br />
IEEE Press.<br />
• Kaustubh Pathak, Andreas Birk, Jann <strong>Poppinga</strong>, and Sören Schwertfeger. 3d forward sensor<br />
modeling and application to occupancy grid based sensor fusion. In IEEE/RSJ Int. Conf. on<br />
Intelligent Robots and Systems, San Diego, Nov 2007.