Mobile robot navigation with distance control

Intelligent systems to increase the road safety have been widely applied in the automotive sector; similarly, they have critical importance in the robotics to navigate the robot safely. Automatic distance control system helps to avoid collision between vehicles. In this paper, we present an algorithm to maintain a distance between the robot and the object. It keeps the autonomous mobile robot at a safe distance from the object. It is implemented in a wheeled mobile robot to track the moving object. The surrounding information is obtained through the range sensors that are mounted at the front side of the robot. The central sensor gives instructions for the forward and backward motion, and the other sensors help for the left and right motion. To avoid collision, safety distance, which makes the movement easy in the out of range, stop, and forward and backward modes, is predefined in the mobile robot. Each time the range data is compared with the predefined distance measurements, and the respected function is activated. The robot is characterized due to low cost and simple control architecture. Different experiments were carried out in the indoor and outdoor environments with different objects. The results have shown that the robot tracks the object correctly by maintaining a constant distance from the followed object.

[1]  Vicente Milanés Montero,et al.  Vision-based active safety system for automatic stopping , 2012, Expert Syst. Appl..

[2]  Michael Himmelsbach,et al.  Autonomous Ground Vehicles—Concepts and a Path to the Future , 2012, Proceedings of the IEEE.

[3]  Irfan Ullah,et al.  Real-time object following fuzzy controller for a mobile robot , 2011, International Conference on Computer Networks and Information Technology.

[4]  Lynne E. Parker,et al.  Guest editorial advances in multirobot systems , 2002, IEEE Trans. Robotics Autom..

[5]  Thomas Bräunl,et al.  Cooperative multi-robot navigation and mapping of unknown terrain , 2011, 2011 IEEE 5th International Conference on Robotics, Automation and Mechatronics (RAM).

[6]  Vicente Milanés Montero,et al.  Intelligent automatic overtaking system using vision for vehicle detection , 2012, Expert Syst. Appl..

[7]  Henk Nijmeijer,et al.  Position Control of a Wheeled Mobile Robot Including Tire Behavior , 2009, IEEE Transactions on Intelligent Transportation Systems.

[8]  Gianluca Antonelli,et al.  A Fuzzy-Logic-Based Approach for Mobile Robot Path Tracking , 2007, IEEE Transactions on Fuzzy Systems.

[9]  Antonios Tsourdos,et al.  Robust Sensor-Based Navigation for Mobile Robots , 2009, IEEE Transactions on Instrumentation and Measurement.

[10]  Woojin Chung,et al.  Safe Navigation of a Mobile Robot Considering Visibility of Environment , 2009, IEEE Transactions on Industrial Electronics.

[11]  Vicente Milanés Montero,et al.  A fuzzy aid rear-end collision warning/avoidance system , 2012, Expert Syst. Appl..

[12]  Seoyong Shin,et al.  Integrated collision avoidance and tracking system for mobile robot , 2012, 2012 International Conference of Robotics and Artificial Intelligence.

[13]  Indra Narayan Kar,et al.  Design and implementation of an adaptive fuzzy logic-based controller for wheeled mobile robots , 2006, IEEE Transactions on Control Systems Technology.

[14]  Michael Beetz,et al.  Cooperative probabilistic state estimation for vision-based autonomous mobile robots , 2002, IEEE Trans. Robotics Autom..

[15]  Terrence Fong,et al.  Multi-robot remote driving with collaborative control , 2003, IEEE Trans. Ind. Electron..

[16]  A. Denker,et al.  Collision Avoidance in Multi-Robot Systems through Cluttered Environments , 1990, Proceedings of the IEEE International Workshop on Intelligent Motion Control.

[17]  Seoyong Shin,et al.  Sensor-Based Robotic Model for Vehicle Accident Avoidance , 2012 .

[18]  S.G. Tzafestas Integrated sensor-based intelligent robot system , 1988, IEEE Control Systems Magazine.

[19]  Chengtao Cai,et al.  Collision Avoidance in Multi-Robot Systems , 2007, 2007 International Conference on Mechatronics and Automation.

[20]  Moshe Kam,et al.  Sensor Fusion for Mobile Robot Navigation , 1997, Proc. IEEE.

[21]  Bing-Fei Wu,et al.  A Real-Time Vision System for Nighttime Vehicle Detection and Traffic Surveillance , 2011, IEEE Transactions on Industrial Electronics.

[22]  Jay A. Farrell,et al.  Real-Time Computer Vision/DGPS-Aided Inertial Navigation System for Lane-Level Vehicle Navigation , 2012, IEEE Transactions on Intelligent Transportation Systems.

[23]  Seoyong Shin,et al.  Sensor-Based Autonomous Robot Navigation with Distance Control , 2012 .

[24]  Irfan Ullah,et al.  A sensor based robotic model for vehicle collision reduction , 2011, International Conference on Computer Networks and Information Technology.