Implementation of a safety system using ir and ultrasonic devices for mobility scooter obstacle collision avoidance

In this study we propose an approach for increasing mobility scooter safety by detecting and avoiding obstacles. The detection system is based on obstacle detection and implemented using infrared and ultrasonic devices. The system is fully embedded and is composed of six infrared and three ultrasonic devices which allow: far detection for crossing objects or normal speed obstacle detection; close detection for low speed obstacles; side obstacle detection when turning. Three experiments have been carried out using our system in an indoor environment using different object shapes and sizes, crossing distances and turning angles. The system was able to detect all obstacles in the mobility scooters path with the exception of transparent flat surfaces. Obstacles passing in front were also successfully detected and when turning into walls the system correctly detected them.

[1]  Hung Nguyen,et al.  In search of a cost effective way to develop autonomous floor mapping robots , 2011, 2011 IEEE International Symposium on Robotic and Sensors Environments (ROSE).

[2]  T. Tomizawa,et al.  Development of an intelligent mobility scooter , 2012, 2012 IEEE International Conference on Mechatronics and Automation.

[3]  Benjamin Kuipers,et al.  Building Local Safety Maps for a Wheelchair Robot using Vision and Lasers , 2006, The 3rd Canadian Conference on Computer and Robot Vision (CRV'06).

[4]  M. Jallouli,et al.  Wheelchair obstacle avoidance based on fuzzy controller and ultrasonic sensors , 2013, 2013 International Conference on Computer Applications Technology (ICCAT).

[5]  Hiroaki Ikeda,et al.  Compact and high-precision range finder with wide dynamic range and its application , 1992 .

[6]  R.C. Luo,et al.  Multisensor controlled obstacle avoidance and navigation of intelligent security robot , 2005, 31st Annual Conference of IEEE Industrial Electronics Society, 2005. IECON 2005..

[7]  Andrew Starr,et al.  A Review of data fusion models and architectures: towards engineering guidelines , 2005, Neural Computing & Applications.

[8]  Dave Tahmoush,et al.  Automotive GMTI radar for object and human avoidance , 2011, 2011 IEEE RadarCon (RADAR).

[9]  Zi-Xing Cai,et al.  Detection and tracking of moving object with a mobile robot using laser scanner , 2008, 2008 International Conference on Machine Learning and Cybernetics.

[10]  T. Dutta,et al.  Utilization of ultrasound sensors for anti-collision systems of powered wheelchairs , 2005, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[11]  Takashi Masuzawa,et al.  Development of a Safety Driving System for Electric Wheelchair , 2009 .

[12]  Hai Huang,et al.  The laser line object detection method in an anti-collision system for powered wheelchairs , 2005, 9th International Conference on Rehabilitation Robotics, 2005. ICORR 2005..

[13]  Hung T. Nguyen,et al.  Spherical vision cameras in a semi-autonomous wheelchair system , 2010, 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology.