Development of Mobile Robot “SARA” that Completed Mission in Real World Robot Challenge 2014
Naoki Akai*, Kenji Yamauchi*, Kazumichi Inoue**, Yasunari Kakigi*, Yuki Abe*, and Koichi Ozaki*
*Graduate School of Engineering, Utsunomiya University
7-1-2 Yoto, Utsunomiya-shi, Tochigi 321-8585, Japan
**AIM Co., Ltd.
2333 Yana, Oyama-shi, Tochigi 323-0158, Japan
View of SARA with and without cowl
Held in Japan every year since 2007, the Real World Robot Challenge (RWRC) is a technical challenge for mobile robots. Every robot is given the missions of traveling a long distance and finding specific persons autonomously. The robots must also have an affinity for people and be remotely monitored. In order to complete the missions, we developed a new mobile robot, SARA, which we entered in RWRC 2014. The robot successfully completed all of the missions of the challenge. In this paper, the systems we implemented are detailed. Moreover, results of experiments and of the challenge are presented, and knowledges we gained through the experience are discussed.
-  K. Nagatani et al., “Sensor information processing in robot competitions and real world robot challenges,” Advanced Robotics, Vol.26, No.14, pp. 1539-1554, 2012.
-  N. Akai et al., “Autonomous navigation based on magnetic and geometric landmarks on environmental structure in real world,” J. of Robotics and Mechatronics, Vol.26, No.2, pp. 158-165, 2014.
-  K. Yamauchi et al., “Person detection method based on color layout in real world robot challenge 2013,” J. of Robotics and Mechatronics, Vol.26, No.2, pp. 151-157, 2014.
-  K. Inoue et al., “Proposal and consideration of design policy for autonomous mobile robots in real world robot challenge,” J. of the Robotics Society of Japan, Vol.30, No.3, pp. 234-244, 2012 (in Japanese).
-  N. Akai et al., “Implementation of magnetic navigation method based on experimental analysis of magnetic field,” J. of the Robotics Society of Japan, Vol.32, No.4, pp. 395-402, 2014 (in Japanese).
-  T. Yoshida et al., “A sensor platform for outdoor navigation using gyro-assisted odometry and roundly-swinging 3D laser scanner,” Int. Conf. on Intelligent Robots and Systems, pp. 1414-1420, 2010.
-  T. Suzuki et al., “Autonomous navigation of a mobile robot based on GNSS/DR integration in outdoor environments,” J. of Robotics and Mechatronics, Vol.26, No.2, pp. 214-224, 2014.
-  M. Tomono et al., “Analysis and design of outdoor navigation system at the Tsukuba challenge,” J. of the Robotics Society of Japan, Vol.30, No.3, pp. 262-270 (in Japanese).
-  S. A. Rahok et al., “Navigation using an environmental magnetic field for outdoor autonomous mobile robots,” Advanced Robotics, Vol.26, Nos.3-4, pp. 1751-1771, 2011.
-  N. Akai et al., “Monte Carlo localization using magnetic sensor and LIDAR for real world navigation,” Int. Symp. on System Integration, pp. 682-687, 2013.
-  F. Dellaert et al., “Monte Carlo localization for mobile robots,” Int. Conf. on Robotics and Automation, Vol.2, pp. 1322-1328, 1999.
-  K. Yamazaki et al., “Analysis of magnetic disturbance due to buildings,” IEEE Trans. on Magnetics Vol.25, pp. 4006-4008, 1989.
-  A. Doucet et al., “Sequential Monte Carlo Methods in Practice,” Springer, 2001.
-  M. Yokozuka et al., “Robotic wheelchair with autonomous traveling capability for transportation assistance in an urban environment.” Int. Conf. on Intelligent Robots and Systems, pp. 2234-2241, 2012.
-  O. Khatib, “Real-time obstacle avoidance for manipulators and mobile robots,” Int. Conf. on Robotics and Automation, Vol.2, pp. 500-505, 1985.
-  D. Fox et al., “The dynamic window approach to collision avoidance,” IEEE Robotics and Automation, Vol.4, No.1, 1997.
-  M. Yokozuka et al., “A reasonable path planning via path energy minimization,” J. of Robotics and Mechatronics, Vol.26, No.2, pp. 236-244, 2014.
-  M. Bertozzi et al., “Pedestrian detection in infrared images,” Proc. of the IEEE Intelligent Vehicles Symposium, pp. 662-667, 2003.
-  N. Dalal et al., “Histogram of oriented gradients for human detection,” Computer Society Conf. on Computer Vision and Pattern Recognition, Vol.1, pp. 886-893, 2005.
-  J. Eguchi et al., “Development of the autonomous mobile robot for target-searching in urban areas in the Tsukuba Challenge 2013,” J. of Robotics and Mechatronics, Vol.26, No.2, pp. 166-176, 2014.