Haptic recognition and mapping of driving road environment by haptograph

Recently, human cooperative robots are desired in an aging society. In particular, recognition performance of environment is the most important. Visual and/or auditory sensors are used to recognize the environment; however, they are not able to recognize contact information. Tactile and/or haptic information is very important for action in unknown environment. The paper gives the haptic sensation to a robot. Furthermore, the obtained haptic information is visualized by haptograph. The haptograph is useful for haptic mapping of environment and trajectory planning for a mobile robot. The experimental results show the viability of the proposed method.

[1]  F.L. Lewis,et al.  Localization of a Wireless Sensor Network with Unattended Ground Sensors and Some Mobile Robots , 2006, 2006 IEEE Conference on Robotics, Automation and Mechatronics.

[2]  H. Mizumoto,et al.  Binocular robot vision system with shape recognition , 2007, 2007 International Conference on Control, Automation and Systems.

[3]  野間 春生,et al.  Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems 参加報告 , 1997 .

[4]  Kouhei Ohnishi,et al.  Advanced Motion Control for Wheelchair in Unknown Environment , 2006, 2006 IEEE International Conference on Systems, Man and Cybernetics.

[5]  Lynette A. Jones,et al.  Tactile Vocabulary for Tactile Displays , 2007, Second Joint EuroHaptics Conference and Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems (WHC'07).

[6]  Kouhei Ohnishi,et al.  Motion control for advanced mechatronics , 1996 .

[7]  Zhiwei Luo,et al.  Development of Soft Areal Tactile Sensors for Human-Interactive Robots , 2006, 2006 5th IEEE Conference on Sensors.

[8]  H. Mizumoto,et al.  Binocular Robot Vision System with Shape Recognition , 2006, 2006 SICE-ICASE International Joint Conference.

[9]  Xiaoping Yun,et al.  Internal dynamics of a wheeled mobile robot , 1993, Proceedings of 1993 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS '93).

[10]  Huosheng Hu,et al.  FPGA-based colour image classification for mobile robot navigation , 2005, 2005 IEEE International Conference on Industrial Technology.

[11]  Jianwei Zhang,et al.  Visual Servoing to Help Camera Operators Track Better , 2006, 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[12]  Anders Heyden,et al.  Extensions of Plane-Based Calibration to the Case of Translational Motion in a Robot Vision Setting , 2006, IEEE Transactions on Robotics.

[13]  Dinesh K. Pai,et al.  Robotic mapping of friction and roughness for reality-based modeling , 2001, Proceedings 2001 ICRA. IEEE International Conference on Robotics and Automation (Cat. No.01CH37164).

[14]  Jianwei Zhang,et al.  Stable Symmetry Feature Detection and Classification in Panoramic Robot Vision Systems , 2006, 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[15]  Kiyoshi Ohishi,et al.  Modal System Design of Multirobot Systems by Interaction Mode Control , 2007, IEEE Transactions on Industrial Electronics.

[16]  S. Katsura,et al.  Modal system design of multi-robot systems by interaction mode control , 2006, 9th IEEE International Workshop on Advanced Motion Control, 2006..

[17]  Jian Gao,et al.  Vision Based Intelligent Control for Mobile Robot , 2006, 2006 6th World Congress on Intelligent Control and Automation.

[18]  Hirokazu Seki,et al.  Novel Straight Road Driving Control of Power Assisted Wheelchair Based on Disturbance Estimation of Right and Left Wheels , 2006 .

[19]  Min-Yong Park,et al.  Outdoor Navigation of a Mobile Robot Using Differential GPS and Curb Detection , 2007, Proceedings 2007 IEEE International Conference on Robotics and Automation.

[20]  Byung Kook Kim,et al.  Near-time-optimal trajectory planning for wheeled mobile robots with translational and rotational sections , 2001, IEEE Trans. Robotics Autom..