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Journal of Robotics
Volume 2011 (2011), Article ID 679875, 6 pages
The Need for High-Fidelity Robotics Sensor Models
1Mobility Systems Branch, Geotechnical and Structures Laboratory, US Army Engineer Research and Development Center, 3909 Halls Ferry Road, Vicksburg, MS 39180, USA
2National Robotics Engineer Center, Carnegie Mellon University, Ten 40th street, Pittsburgh, PA 15201, USA
Received 11 January 2011; Accepted 7 September 2011
Academic Editor: Lyle N. Long
Copyright © 2011 Phillip J. Durst et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
- A. Vadlamani, M. Smearcheck, and M. U. De Haag, “Preliminary design and analysis of a lidar based obstacle detection system,” in Proceedings of the 24th Digital Avionics Systems Conference, vol. 1, pp. 6.B.2–61-14, November 2005.
- R. Telgarsky, M. C. Gates, C. Thompson, and J. N. Sanders-Reed, “High fidelity ladar simulation,” in Proceedings of the Laser Radar Technology and Applications IX, vol. 5412 of Proceedings of SPIE, pp. 194–207, April 2004.
- E. B. Wilson, “Real-time correlative scan matching,” in Proceedings of the IEEE International Conference on Robotics and Automation, pp. 4387–4393, May 2009.
- J. Tuley, N. Vandapel, and M. Hebert, “Analysis and removal of artifacts in 3-D LADAR data,” in Proceedings of the IEEE International Conference on Robotics and Automation (ICRA '05), pp. 2203–2210, April 2005.
- A. Stentz, J. Bares, T. Pilarski, and D. Stager, “The crusher system for autonomous navigation,” in Proceedings of the Unmanned Systems North America Conference, pp. 972–986, August 2007.
- D. Ferguson and A. Stentz, “Using interpolation to improve path planning the field D* algorithm,” Journal of Field Robotics, vol. 23, no. 2, pp. 79–101, 2006.
- T. Lee, U. Nehmzow, and R. Hubbold, “Mobile robot simulation by means of acquired neural network models,” in Proceedings of the 12th European Simulation Multiconference, 1998.
- R. A. Brook, “Artificial life and real robots,” in Proceedings of the 1st European Conference on Artificial Life, pp. 3–10, 1992.
- E. Gat, “Towards principled experimental study of autonomous mobile robots,” Autonomous Robots, vol. 2, no. 3, pp. 179–189, 1995.
- U. Nehmzow, “Quantitative analysis of robot-environment interaction-towards “scientific mobile robotics”,” Robotics and Autonomous Systems, vol. 44, no. 1, pp. 55–68, 2003.
- U. Nehmzow, “Quantitative analysis of robot-environment interaction-on the difference between simulations and the real thing,” in Proceedings of the Eurobot, 2001.
- S. Carpin, T. Stoyanov, Y. Nevatia, M. Lewis, and J. Want, “Quantitative assessments of USARSim accuracy,” in Proceedings of the PerMIS, 2006.
- SICK, 2006, http://sicktoolbox.sourceforge.net/docs/sick-lms-technical-description.pdf.
- S. Balakirsky, S. Carpin, G. Dimitoglou, and B. Balaguer, “From simulation to real robots with predictable results: methods and examples,” in Performance Evaluation and Benchmarking of Intelligent Systems, pp. 113–137, Springer, New York, NY, USA, 2009.
- B. Gerkey, R. Vaughan, and A. Howard, “The player/stage project: tools for multi-robot and distributed sensor systems,” in Proceedings of the International Conference on Advanced Robotics, pp. 317–323, 2003.