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A complete navigation system for goal acquisition in unknown environments

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Abstract

Most autonomous outdoor navigation systems tested on actual robots have centered on local navigation tasks such as avoiding obstacles or following roads. Global navigation has been limited to simple wandering, path tracking, straight-line goal seeking behaviors, or executing a sequence of scripted local behaviors. These capabilities are insufficient for unstructured and unknown environments, where replanning may be needed to account for new information discovered in every sensor image. To address these problems, we have developed a complete system that integrates local and global navigation. The local system uses a scanning laser rangefinder to detect obstacles and recommend steering commands to ensure robot safety. These obstacles are passed to the global system which stores them in a map of the environment. With each addition to the map, the global system uses an incremental path planning algorithm to optimally replan the global path and recommend steering commands to reach the goal. An arbiter combines the steering recommendations to achieve the proper balance between safety and goal acquisition. This system was tested on a real robot and successfully drove it 1.4 kilometers to find a goal given no a priori map of the environment.

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References

  • Bhatt, R., Venetsky, L., Gaw, D., Lowing, D., and Meystel, A. 1987. A Real-Time Pilot for an Autonomous Robot.Proceedings of IEEE Conference on Intelligent Control.

  • Chatila, R., Devy, M., and Herrb, M. 1994. Perception System and Functions for Autonomous Navigation in a Natural Environment.Proceedings of CIRFFSS.

  • Daily, M., Harris, J., Keirsey, D., Olin, K., Payton, D., Reiser, K., Rosenblatt, J., Tseng, D., and Wong, V. 1988. Autonomous Cross Country Navigation with the ALV.Proceedings of the IEEE International Conference on Robotics and Automation.

  • Dickmanns, E.D. and Zapp, A. 1986. A Curvature-Based Scheme for Improving Road Vehicle Guidance by Computer Vision.Proceedings of the SPIE Conference on Mobile Robots.

  • Dunlay, R.T. and Morgenthaler, D.G. 1986. Obstacle Avoidance on Roadways Using Range Data.Proceedings of SPIE Conference on Mobile Robots.

  • Fedor, C. 1993. TCX, Task Communications User's Manual. Internal Report. The Robotics Institute, Carnegie Mellon.

  • Feng, D., Singh, S., and Krogh, B. 1990. Implementation of Dynamic Obstacle Avoidance on the CMU Navlab.Proceedings of IEEE Conference on Systems Engineering.

  • Franke, U., Fritz, H., and Mehring, S. 1991. Long Distance Driving with the Daimler-Benz Autonomous Vehicle VITA. PROMETHEUS Workshop, Grenoble.

    Google Scholar 

  • Gat, E., Slack, M.G., Miller, D.P., and Firby, R.J. 1990. Path Planning and Execution Monitoring for a Planetary Rover.Proceedings of the IEEE International Conference on Robotics and Automation.

  • Goto, Y. and Stentz, A. 1987. Mobile Robot Navigation: The CMU System.IEEE Expert, 2(4).

  • Hebert, M. 1994. Pixel-Based Range Processing for Autonomous Driving.Proceedings of the IEEE International Conference on Robotics and Automation.

  • Hebert, M. and Krotkov, E. 1992. 3D Measurements from Imaging Laser Radars.Image and Vision Computing, 10(3).

  • Keirsey, D.M., Payton, D.W., and Rosenblatt, J.K. 1988. Autonomous Navigation in Cross-Country Terrain. In Image Understanding Workshop, Cambridge, MA.

    Google Scholar 

  • Kelly, A.J. 1994. RANGER—An Intelligent Predictive Controller for Unmanned Ground Vehicles. The Robotics Institute, Carnegie Mellon.

  • Kluge, K. 1993. YARF: An Open-Ended Framework for Robot Road Following. Ph.D. Dissertation, CMU-CS-93-104, School of Computer Science, Carnegie Mellon University.

  • Korf, R.E. 1987. Real-Time Heuristic Search: First Results.Proceedings of the Sixth National Conference on Artificial Intelligence.

  • Langer, D., Rosenblatt, J.K., and Hebert, M. 1994. An Integrated System for Autonomous Off-Road Navigation.Proceedings of the IEEE International Conference on Robotics and Automation.

  • Latombe, J.-C. 1991. Robot Motion Planning. Kluwer Academic Publishers.

  • Lumelsky, V.J. and Stepanov, A.A. 1986. Dynamic Path Planning for a Mobile Automation with Limited Information on the Environment.IEEE Transactions on Automatic Control, AC-31(11).

  • Matthies, L. 1992. Stereo Vision for Planetary Rovers: Stochastic Modeling to Near Real-Time Implementation.International Journal of Computer Vision, 8(1).

  • McTamaney, L.S. 1987. Mobile Robots: Real-Time Intelligent Control.IEEE Expert, 2(4).

  • Nilsson, N.J. 1980. Principles of Artificial Intelligence. Tioga Publishing Company.

  • Payton, D.W., Rosenblatt, J.K., and Keirsey, D.M. 1990. Plan Guided Reaction.IEEE Transactions on Systems, Man and Cybernetics, 20(6):1370–1382.

    Google Scholar 

  • Pirzadeh, A. and Snyder, W. 1990. A Unified Solution to Coverage and Search in Explored and Unexplored Terrains Using Indirect Control.Proceedings of the IEEE International Conference on Robotics and Automation.

  • Pomerleau, D.A. 1991. Efficient Training of Artificial Neural Networks for Autonomous Navigation.Neural Computation, 3(1).

  • Rosenblatt, J.K. and Payton, D.W. 1989. A Fine-Grained Alternative to the Subsumption Architecture for Mobile Robot Control. InProceedings of the IEEE/INNS International Joint Conference on Neural Networks, Washington DC, 2:317-324.

  • Singh, S., Feng, D., Keller, P., Shaffer, G., Shi, W.F., Shin, D.H., West, J., and Wu, B.X. 1991. A System for Fast Navigation of Autonomous Vehicles. Robotics Institute Technical Report CMU-RI-TR-91-20, Carnegie Mellon University.

  • Stentz, A., Brumitt, B.L., Coulter, R.C., and Kelly, A. 1992. An Autonomous System for Cross-Country Navigation.Proceedings of the SPIE Conference on Mobile Robots.

  • Stentz, A. 1994. Optimal and Efficient Path Planning for Partially-Known Environments.Proceedings of the IEEE International Conference on Robotics and Automation.

  • Thorpe, C., Amidi, O., Gowdy, J., Hebert, M., and Pomerleau, D. 1991. Integrating Position Measurement and Image Understanding for Autonomous Vehicle Navigation.Proceedings of the Workshop on High Precision Navigation, Springer-Verlag Publisher.

  • Wilcox, B., Matthies, L., Gennery, D., Cooper, B., Nguyen, T., Litwin, T., Mishkin, A., and Stone, H. 1992. Robotic Vehicles for Planetary Exploration.Proceedings of the IEEE International Conference on Robotics and Automation.

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  1. The Robotics Institute, Carnegie Mellon University, 15213, Pittsburgh, Pennsylvania, USA

    Anthony Stentz & Martial Hebert

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  1. Anthony Stentz
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  2. Martial Hebert
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Stentz, A., Hebert, M. A complete navigation system for goal acquisition in unknown environments. Auton Robot 2, 127–145 (1995). https://doi.org/10.1007/BF00735431

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