1. Introduction. - 1. 1. Mobile Robots. - 1. 2. Overview. - 1. 3. Acknowledgments. - 2. Color Vision for Road Following. - 2. 1. Introduction. - 2. 2. SCARF. - 2. 3. UNSCARF. - 2. 4. Results and Conclusions. - 2. 5. References. - 3. Explicit Models for Robot Road Following. - 3. 1 Implicit Models Considered Harmful. - 3. 2 Systems Models and Assumptions. - 3. 3 FERMI. - 3. 4 References. - 4. An Approach to Knowledge-Based Interpretation of Outdoor Natural Color Road Scenes. - 4. 1. Abstract. - 4. 2. Introduction. - 4. 3. Related Work. - 4. 4. Adjustable Explicit Scene Models and the Interpretation Cycle. - 4. 5. System Overview. - 4. 6. Results of the Road Scene Interpretation. - 4. 7. The Road Scene Interpretation System in Detail. - 4. 8. Future Work. - 4. 9. Conclusion. - 4. 10. Acknowledgement. - 4. 11. References. - 5. Neural Network Based Autonomous Navigation. - 5. 1. Introduction. - 5. 2. Network Architecture. - 5. 3. Training And Performance. - 5. 4. Network Representation. - 5. 5. Discussion And Extensions. - 5. 6. Conclusion. - 5. 7. References. - 6. Car Recognition for the CMU Navlab. - 6. 1 Introduction. - 6. 2 Related work. - 6. 3 The LASSIE object recognition program. - 6. 4 Results. - 6. 5 Directions for future work. - 6. 6 Summary. - 6. 7 References. - 7. Building and Navigating Maps of Road Scenes Using Active Range and Reflectance Data. - 7. 1. Introduction. - 7. 2. Following roads using active reflectance images. - 7. 3. Building maps from range and reflectance images. - 7. 4. Map-based road following. - 7. 5. Conclusion. - 7. 6. References. - 8. 3-D Vision Techniques for Autonomous Vehicles. - 8. 1. Introduction. - 8. 2. Active range and reflectance sensing. - 8. 3. Terrain representations. - 8. 4. Combining multiple terrain maps. - 8. 5. Combining range and intensity data. - 8. 6. Conclusion. - 8. 7. References. - 9. The CODGER System for Mobile RobotNavigation. - 9. 1 Introduction. - 9. 2 Overview of the CODGER System. - 9. 3 Data Storage and Transfer. - 9. 4 Geometric Representation and Reasoning. - 9. 5 Conclusions. - 9. 6 References. - 10. The Driving Pipeline: A Driving Control Scheme for Mobile Robots. - 10. 1 Introduction. - 10. 2 Processing Steps and Driving Unit. - 10. 3 Continuous Motion Adaptive Control and the Driving Pipeline. - 10. 4 The Driving Pipeline in Action: Experimental Results. - 10. 5 Conclusion. - 10. 6 References. - 11. Multi-Resolution Constraint Modeling for Mobile Robot Planning. - 11. 1 Introduction. - 11. 2 The Local Navigation Problem. - 11. 3 Finding Trajectories. - 11. 4 Experiments. - 11. 5 Conclusions. - 11. 6 Acknowledgements. - 11. 7 References. - 12. Navlab: An Autonomous Navigation Testbed. - 12. 1 Introduction. - 12. 2 Controller. - 12. 3 Vehicle Shell. - 12. 4 Locomotion. - 12. 5 Electrical System. - 12. 6 Telemetry. - 12. 7 Perceptive Sensing and Computing. - 12. 8 Conclusion. - 13. Vehicle and Path Models for Autonomous Navigation. - 13. 1 Introduction. - 13. 2 Vehicle Representation. - 13. 3 Path Representation. - 13. 4 Path Tracking. - 13. 5 Results. - 13. 6 Conclusions. - 13. 7 References. - 14. The Warp Machine on Navlab. - 14. 1 Introduction. - 14. 2 History of the Warp Machine on Navlab. - 14. 3 FIDO. - 14. 4 SCARF. - 14. 5 ALVINN. - 14. 6 Evaluation of the Warp Machine on Navlab. - 14. 7 Conclusions. - 14. 8 References. - 15. Outdoor Visual Navigation for Autonomous Robots. - 15. 1 Introduction. - 15. 2 Example Systems. - 15. 3 Discussion and Conclusions. - 15. 4 Acknowledgements. - 15. 5 References. Language: English