Dickens, JSGreen, JJVan Wyk, MA2011-10-102011-10-102011-07Dickens, JS, Green, JJ and Van Wyk, MA. 2011. Human detection for underground autonomous mine vehicles using thermal imaging. 26th International Conference on CAD/CAM, Robotics and Factories of the Future (CARs&FOF 2011), Kuala Lumpur, Malaysia, 26-28 July 2011http://hdl.handle.net/10204/521326th International Conference on CAD/CAM, Robotics and Factories of the Future (CARs&FOF 2011), Kuala Lumpur, Malaysia, 26-28 July 2011Underground mine automation has the potential to increase safety, productivity and allow the mining of lower-grade resources. In a mining environment with both autonomous robots and humans, it is essential that the robots are able to detect and avoid people. Current pedestrian detection systems and the reasons that they are inadequate for mining robots are discussed. A system for human detection in underground mines, using a fusion of three-dimensional (3D) information with thermal imaging, is proposed. The system extracts regions of interest and classifies them as human or background. The scene excluding the pedestrians is assumed to be static and is intended to be used to determine the ego motion of the vehicle. In addition to the thermal camera, a distance sensor will provide depth information and allow the calculation of the vehicle and pedestrian velocities. Various classification methods are compared and it is shown that a neural network provides the best results in terms of speed and accuracy. The results of tests on two 3D sensors indicate that further work is required to determine the effect of the harsh environment on the accuracy of the sensors.enUnderground autonomous mine vehiclesThermal imagingMine safetyUnderground miningAutonomous robotsObstacle detectionHuman trackingRoboticsMine vehiclesConference PresentationDickens, J., Green, J., & Van Wyk, M. (2011). Human detection for underground autonomous mine vehicles using thermal imaging. http://hdl.handle.net/10204/5213Dickens, JS, JJ Green, and MA Van Wyk. "Human detection for underground autonomous mine vehicles using thermal imaging." (2011): http://hdl.handle.net/10204/5213Dickens J, Green J, Van Wyk M, Human detection for underground autonomous mine vehicles using thermal imaging; 2011. http://hdl.handle.net/10204/5213 .TY - Conference Presentation AU - Dickens, JS AU - Green, JJ AU - Van Wyk, MA AB - Underground mine automation has the potential to increase safety, productivity and allow the mining of lower-grade resources. In a mining environment with both autonomous robots and humans, it is essential that the robots are able to detect and avoid people. Current pedestrian detection systems and the reasons that they are inadequate for mining robots are discussed. A system for human detection in underground mines, using a fusion of three-dimensional (3D) information with thermal imaging, is proposed. The system extracts regions of interest and classifies them as human or background. The scene excluding the pedestrians is assumed to be static and is intended to be used to determine the ego motion of the vehicle. In addition to the thermal camera, a distance sensor will provide depth information and allow the calculation of the vehicle and pedestrian velocities. Various classification methods are compared and it is shown that a neural network provides the best results in terms of speed and accuracy. The results of tests on two 3D sensors indicate that further work is required to determine the effect of the harsh environment on the accuracy of the sensors. DA - 2011-07 DB - ResearchSpace DP - CSIR KW - Underground autonomous mine vehicles KW - Thermal imaging KW - Mine safety KW - Underground mining KW - Autonomous robots KW - Obstacle detection KW - Human tracking KW - Robotics KW - Mine vehicles LK - https://researchspace.csir.co.za PY - 2011 T1 - Human detection for underground autonomous mine vehicles using thermal imaging TI - Human detection for underground autonomous mine vehicles using thermal imaging UR - http://hdl.handle.net/10204/5213 ER -