Implementation of Mobile Robot Control in Intelligent Space

In this paper we present the implementation of mobile robot control in the intelligent space (iSpace). The mobile robot in iSpace is primarily used as a mean of offering physical services to users, or as a mobile sensor for providing more details about the space. On the other hand, the distributed sensors in iSpace offer advantages in standard robot control tasks. In this paper the details of the engagement of mobile robots in iSpace are given. Moreover, the details of the implementation of the mobile robot localization mapping and navigation are described in detail and experimental results are given

[1]  S.K. Kundu,et al.  Development of a 2DOF Inner Skeleton Robot for Forearm Motion Assist , 2006, 2006 SICE-ICASE International Joint Conference.

[2]  Roland Siegwart,et al.  Smooth and efficient obstacle avoidance for a tour guide robot , 2003, 2003 IEEE International Conference on Robotics and Automation (Cat. No.03CH37422).

[3]  Luis Montano,et al.  Motion planning in dynamic environments using the velocity space , 2005, 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[4]  Joo-Ho Lee,et al.  Intelligent Space — concept and contents , 2002, Adv. Robotics.

[5]  Y. Marutani,et al.  Development of 5-Axis Friction Stir Welding System , 2006, 2006 SICE-ICASE International Joint Conference.

[6]  Marilena Vendittelli,et al.  Real-time map building and navigation for autonomous robots in unknown environments , 1998, IEEE Trans. Syst. Man Cybern. Part B.

[7]  Anthony Stentz,et al.  Optimal and efficient path planning for partially-known environments , 1994, Proceedings of the 1994 IEEE International Conference on Robotics and Automation.

[8]  Wolfram Burgard,et al.  Probabilistic Robotics (Intelligent Robotics and Autonomous Agents) , 2005 .

[9]  Wolfram Burgard,et al.  The dynamic window approach to collision avoidance , 1997, IEEE Robotics Autom. Mag..

[10]  Th Fraichard Trajectory Planning in Dynamic Workspaces: a `state-time Space' Approach Trajectory Planning in Dynamic Workspaces: a `state-time Space' Approach , 1997 .

[11]  Axel Pinz,et al.  A comparison of three uncertainty calculi for building sonar-based occupancy grids , 2001, Robotics Auton. Syst..

[12]  Roland Siegwart,et al.  An Interpolated Dynamic Navigation Function , 2005, Proceedings of the 2005 IEEE International Conference on Robotics and Automation.

[13]  Wolfram Burgard,et al.  Map learning and high-speed navigation in RHINO , 1998 .