Low Cost, Robust and Real Time System for Detecting and Tracking Moving Objects to Automate Cargo Handling in Port Terminals
The presented paper addresses the problem of detecting and tracking moving objects for autonomous cargo handling in port terminals using a perception system which input data is a single layer laser scanner. A computationally low cost and robust Detection and Tracking Moving Objects (DATMO) algorithm is presented to be used in autonomous guided vehicles and autonomous trucks for efficient transportation of cargo in ports. The method first detects moving objects and then tracks them, taking into account that in port terminals the structure of the environment is formed by containers and that the moving objects can be trucks, AGV, cars, straddle carriers and people among others. Two approaches of the DATMO system have been tested, the first one is oriented to detect moving obstacles and focused on tracking and filtering those detections; and the second one is focused on keepking targets when no detections are provided. The system has been evaluated with real data obtained in the CTT port terminal in Hengelo, the Netherlands. Both methods have been tested in the dataset with good results in tracking moving objects.
KeywordsObject detection Object tracking DATMO Multi-hypothesistracking Autonomous driving Autonomous transportation of cargo
Unable to display preview. Download preview PDF.
- 1.Arras, K.O., Grzonka, S., Luber, M., Burgard, W.: Efficient people tracking in laser range data using a multi-hypothesis leg-tracker with adaptive occlusion probabilities. In: IEEE International Conference on Robotics and Automation (2008)Google Scholar
- 3.Corominas-Murtra, A., Pages, J., Pfeiffer, S.: Multi-target & multi-detector people tracker for mobile robots. In: IEEE European Conference on Mobile Robotics (2015)Google Scholar
- 6.Kim, K.H., Jeon, S.M., Ryu, K.R.: Deadlock prevention for automated guided vehicles in automated container terminals. In: Container Terminals and Cargo Systems: Design, Operations Management, and Logistics Control Issues (2007)Google Scholar
- 8.Mendes, A., Bento, L., Nunes, U.: Multi-target detection and tracking with a laserscanner. In: IEEE Intelligent Vehicles Symposium, pp. 796–801 (2004)Google Scholar
- 9.Mertz, C., Navarro-Serment, L.E., Maclachlan, R., Rybski, P., Steinfeld, A., Urmson, C., Vandapel, N., Hebert, M., Thorpe, C., Duggins, D., Gowdy, J.: Moving Object Detection with Laser Scanners. Journal of Field Robotics, 1–27 (2012)Google Scholar
- 11.Roodbergen, K.J., Vis, I.F.: A survey of literature on automated storage and retrieval systems (2009)Google Scholar