Outdoor navigation of mobile robots

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64, [64]
Acta polytechnica Scandinavica. Me, Mechanical engineering series, 155
AGVs in the manufacturing industry currently constitute the largest application area for mobile robots. Other applications have been gradually emerging, including various transporting tasks in demanding environments, such as mines or harbours. Most of the new potential applications require a free-ranging navigation system, which means that the path of a robot is no longer bound to follow a buried inductive cable. Moreover, changing the route of a robot or taking a new working area into use must be as effective as possible. These requirements set new challenges for the navigation systems of mobile robots. One of the basic methods of building a free ranging navigation system is to combine dead reckoning navigation with the detection of beacons at known locations. This approach is the backbone of the navigation systems in this study. The study describes research and development work in the area of mobile robotics including the applications in forestry, agriculture, mining, and transportation in a factory yard. The focus is on describing navigation sensors and methods for position and heading estimation by fusing dead reckoning and beacon detection information. A Kalman filter is typically used here for sensor fusion. Both cases of using either artificial or natural beacons have been covered. Artificial beacons used in the research and development projects include specially designed flat objects to be detected using a camera as the detection sensor, GPS satellite positioning system, and passive transponders buried in the ground along the route of a robot. The walls in a mine tunnel have been used as natural beacons. In this case, special attention has been paid to map building and using the map for positioning. The main contribution of the study is in describing the structure of a working navigation system, including positioning and position control. The navigation system for mining application, in particular, contains some unique features that provide an easy-to-use procedure for taking new production areas into use and making it possible to drive a heavy mining machine autonomously at speed comparable to an experienced human driver.
dead reckoning, environment modelling, mobile robot, navigation, position control, sensor fusion
Other note
  • Mäkelä, H., Koskinen, K. (1991) Navigation of Outdoor Mobile Robots Using Dead Reckoning and Visually Detected Landmarks. ICAR'91, Fifth International Conference on Advanced Robotics, June 19-22, 1991, Pisa, Italy, pp. 1151-1156.
  • Mäkelä, H., Koskinen, K., Rintanen, K. (1993) Navigation of a Land Vehicle by Fusing Dead Reckoning and Camera Measurements. 1st IFAC International Workshop on Intelligent Autonomous Vehicles (IAV'93), April 18-21, 1993, Southampton, England, pp. 99-104.
  • Mäkelä, H., Lehtinen, H., Rintanen, K., Koskinen, K. (1995) Navigation System for LHD Machines. 2nd IFAC Conference on Intelligent Autonomous Vehicles (IAV'95), 12-14 June 1995, Espoo, Finland, pp. 314-319.
  • Rintanen, K., Mäkelä, H., Koskinen, K., Puputti, J., Ojala, M. (1996) Development of an Autonomous Navigation System for an Outdoor Vehicle. Control Engineering Practice, vol. 4, no. 4, 1996, pp. 499-505.
  • Mäkelä, H., Kaarmila, P., Koskinen, K. (1998) Convoy Navigation. 3rd IFAC Conference on Intelligent Autonomous Vehicles (IAV'98), 25-27 March 1998, Madrid, Spain, pp. 31-36.
  • Mäkelä, H., von Numers, T. (2001) Development of an Autonomous Outdoor Vehicle for a Steel Plant. Control Engineering Practice 9, 2001, pp. 573-583.
  • Mäkelä, H. (2001) Overview of LHD Navigation Without Artificial Beacons. Robotics and Autonomous Systems 36, 2001, pp. 21-35.
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