Development of an Intelligent Compact Crawler Robot for House Foundation Inspection


  • Keiichiro Masuda Graduate School of Science and Engineering, Hosei University
  • Goragod Pongthanisorn Graduate School of Science and Engineering, Hosei University
  • Genci Capi Graduate School of Science and Engineering, Hosei University


Crawler robot, Deep Learning, House foundation investigation, damage recognition


In this work, we propose a mobile robot for house foundation inspection. The robot can operate in user-controlled mode and in autonomous mode. In user-controlled mode, the developed robot exchange information with the user through a GUI system. In addition, the operator can control the robot remotely. The robot moving trajectory is shown in the developed GUI. In autonomous mode the robot utilizes trained Deep Learning models running in the Raspberry Pi for concrete crack and water leaking detection.  The results show that the proposed system is functioning well in the experimental environment and can be further  expanded for other implementations.


Quy-Hung Vu, Byeong-Sang Kim and Jae-Bok Song, "Autonomous stair climbing algorithm for a small four-tracked robot," 2008 International Conference on Control, Automation and Systems, Seoul, Korea (South), 2008, pp. 2356-2360.

Zhenzhong Yu, Kaiti Cai, Wei Liu, Weicou Zheng, Review of Rescue Robot Technology, Journal of Jiangnan University (Natural Science Edition), 2015,14(04): 498-504.

Hui Zhang, Xiangdong Cai, Dan Hai, Dengke Zhu, Shaoke Qian, Xun Li, Zhiqiang Zheng, NuBot rescue robot overall design , Robot Technique and Application, 2010(04): 17-19.

Homma, K., Yamada, Y., Matsumoto, O., Ono, E., Lee, S., Horimoto, M., & Shiozawa, S. (2009, June). A proposal of a method to reduce burden of excretion care using robot technology. In 2009 IEEE International Conference on Rehabilitation Robotics (pp. 621-625). IEEE.

Michael Baker, Robert Casey et al. ” Improved interfaces for human-robot interaction in urban search and rescue.”, SMC (3) 2004: 2960-2965.

Yugang liu, Goldie Nejat, “Robotic urban search and rescue: A survey from the control perspective”, Journal of Intelligent & Robotics Systems, Vol. 72, Issue 2, pp. 147-165, 2013.

David Erdos, Abraham Erdos, Steve E. Watkins, “An Experimental UAV System for Search and Rescue Challenge”, IEEE Aerospace and Electronic Systems Magazine, Vol.28, Issue 5, pp.32-37, 2013.

Teodor Tomic, Korbinian Schmid, Philipp Lutz, Darius Burschka,Toward a Fully Autonomous UAV: Research Platform for Indoor and Outdoor Urban Search and Rescue”, IEEE Robotics & Automations Magazine, Vol.19, Issue.3, pp. 46-56, 2012.

Ivan Vasilyev, Alla Kashourina, Maxim Krasheninnikov, Ekatherina Smirnova, “Use of Mobile Robots Groups for Rescue Missions in Extreme Climatic Conditions”, 25th DAAAM International Symposium on Intelligent Manufacturing and Automation, pp. 1242 –1246, 2014.

T. Duc Dung, and G. Capi, Application of Neural Networks for Robot 3d Mapping and Annotation Using Depth Image Camera, International Journal of Robotics and Automation, Vol. 37, Issue 6, 2022.

S. Nilwong, D. Hossain, S. Kaneko, G. Capi, Deep Learning-Based Landmark Detection for Mobile Robot Outdoor Localization. Machines 2019, 7, 25.

D. Hossain, G. Capi, “Multiobjective Evolution of Deep Learning Parameters for Robot Manipulator Object Recognition and Grasping”, Advanced Robotics, 32(20): 1090-1101.

W. Qi, Y. Chun, Y. Sheng, G. Zhao and L. Wang, "Stability Analysis of Obstacle Avoidance Ability and Environment Adaptation Modeling of Snake Robot based on Deep Learning and Binocular Vision," 2022 3rd International Conference on Smart Electronics and Communication (ICOSEC), Trichy, India, 2022, pp. 299-3024.