Development of the Autonomous Mobile Robot for Target-Searching in Urban Areas in the Tsukuba Challenge 2013
Junji Eguchi and Koichi Ozaki
Utsunomiya University, 7-1-2 Yoto, Utsunomiya-city, Tochigi 321-8585, Japan
This paper describes a navigation method for autonomous mobile robots and the knowledge obtained through trial runs conducted during the Tsukuba Challenge 2013 whose main tasks were autonomous navigation by robots to a goal and searching for target persons in several urban areas. Accurate maps are an important tool in localization on complex courses. We constructed occupancy grid map making method using laser scanners, gyro-assisted odometry and a DGPS. In trial runs, robots detect target parsons two ways – one involving color detection in images and the other involving laser scanner intensity data. The major problem with these methods is misdetection. To minimize this, we mask areas in which target persons should not exist on occupancy grid maps. Target candidates detected in masked areas are rejected, which indicates the possibility of using accurate occupancy grid maps as a user-friendly graphical interface. This paper focuses on the localization method, the target detection method and autonomous navigation knowledge in common space through the challenge.
-  S. Yuta, M. Mizukawa, and H. Hashimoto, “Tsukuba Challenge: The Purpose and Results,” J. of the Society of Instrument and Control Engineers, Vol.49, No.9, pp. 572-578, 2010 (in Japanese).
-  M. Yokozuka, Y. Suzuki, T. Takei, N. Hashimoto, and O. Matsumoto, “Auxiliary Particle Filter Localization for Intelligent Wheelchair Systems in Urban Environments,” J. of Robotics and Mechatronics, Vol.22, No.6, pp. 758-765, 2010.
-  T. Tomizawa, S. Muramatsu, M. Sato, M. Hirai, S. Kudoh, and T. Suehiro, “Development of an Intelligent Senior-Car in a Pedestrian Walkway,” Advanced robotics, Vol.26, No.14, 2012.
-  H. Date and Y. Takita, “Real world experiments of an autonomous mobile robot in the pedestrian environment,” in: Proc. 5th Int. Conf. on Automation, Robotics and Applications, Wellington, New Zealand, pp. 413-418, 2011.
-  T. Yoshida, K. Irie, E.Koyanagi, and M. Tomono, “An Outdoor Navigation Platform with a 3D Scanner and Gyro-assisted Odometry,” Trans. of the Society of Instrument and Control Engineers, Vol.47, No.10, pp. 493-500, 2011.
-  K. Ohno, T. Tsubouchi, B. Shigematsu, and S. Yuta, “Differential GPS and odometry-based outdoor navigation of a mobile robot,” Advanced robotics, Vol.18, No.6, pp. 611-635, 2004.
-  Y.Morales, E. Takeuchi, and T. Tsubouchi, “Vehicle Localization in Outdoor Woodland Environment with sensor fault detection,” Proc. of the ICRA 2008, pp. 449-454, 2008.
-  M.Montemerlo, S. Thrun, D. Koller, and B.Wegbreit, “FastSLAM: A factored solution to simultaneous mapping and localization,” Proc. National Conf. on Artificial Intelligence (AAAI), 2002.
-  J. Eguchi and K. Ozaki, “Development of Making Method of Occupancy Grid Map for Localization by Combination with DGPS and Scan Matching,” J. of Robotics and Mechatronics, Vol.25, No.3, 2013.
-  S. Thrun, W. Burgard, and D. Fox, “Probabilistic Robotics,” The MIT Press, 2005.
-  T. Suzuki et al., “The Possibility of the Precise Positioning andMultipath Error Mitigation in the Real-time,” The 2004 Int. Symposium on GNSS/GPS, 2004.
-  E. Takeuchi, M. Yamazaki, K. Ohno, and S. Tadokoro, “GPS Measurement Model with Satellite Visibility using 3D Map for Particle Filter,” 2011 IEEE Int. Conf. on Robotics and Biomimetics (ROBIO2011), 2011.
-  J. Eguchi and K. Ozaki, “Development of Occupancy Grid Map Making Method Based on DGPS Measurement Data Extracted by Accuracy Evaluation,” Trans. of the Japan Society of Mechanical Engineers, Series C, Vol.78, No.794, pp. 3459-3468, 2012 (in Japanese).
-  K. Irie, T. Yoshida, E. Koyanagi, and M. Tomono, “A Localization Method Using Gyro-assisted Odometry and 3D Laser Scanner Considering Gyro Drift Error,” 2010 JSME Conf. on Robotics and Mechatronics, 1A1-E01, 2010 (in Japanese).
-  A.Watanabe, S. Bando, K. Shinada, and S. Yuta, “Road-Following-Based Navigation in Park and Street with Finding Intersection and Orientation Detection,” J. of Robotics Society of Japan, Vol.30, No.3, pp. 271-279, 2012 (in Japanese).
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