ALVINN: an autonomous land vehicle in a neural network
Advances in neural information processing systems 1
An intelligent, predictive control approach to the high-speed cross-country autonomous navigation problem
Autonomous Cross-Country Navigation: An Integrated Perception and Planning System
IEEE Expert: Intelligent Systems and Their Applications
Algorithms for Inverse Reinforcement Learning
ICML '00 Proceedings of the Seventeenth International Conference on Machine Learning
Apprenticeship learning via inverse reinforcement learning
ICML '04 Proceedings of the twenty-first international conference on Machine learning
Stereo-Based Tree Traversability Analysis for Autonomous Off-Road Navigation
WACV-MOTION '05 Proceedings of the Seventh IEEE Workshops on Application of Computer Vision (WACV/MOTION'05) - Volume 1 - Volume 01
Toward Reliable Off Road Autonomous Vehicles Operating in Challenging Environments
International Journal of Robotics Research
ICML '06 Proceedings of the 23rd international conference on Machine learning
Stanley: The robot that won the DARPA Grand Challenge: Research Articles
Journal of Robotic Systems - Special Issue on the DARPA Grand Challenge, Part 2
Learning and prediction of slip from visual information: Research Articles
Journal of Field Robotics - Special Issue on Space Robotics
A Generative Model of Terrain for Autonomous Navigation in Vegetation
International Journal of Robotics Research
Learning traversability models for autonomous mobile vehicles
Autonomous Robots
Learning long-range vision for autonomous off-road driving
Journal of Field Robotics - Special Issue on LAGR Program, Part II
Global planning on the Mars Exploration Rovers: Software integration and surface testing
Journal of Field Robotics - Special Issue on Space Robotics, Part II
Terrain Adaptive Navigation for planetary rovers
Journal of Field Robotics - Special Issue on Space Robotics, Part II
Online terrain parameter estimation for wheeled mobile robots with application to planetary rovers
IEEE Transactions on Robotics
Robot self-initiative and personalization by learning through repeated interactions
Proceedings of the 6th international conference on Human-robot interaction
Autonomous over-the-horizon navigation using LIDAR data
Autonomous Robots
Reinforcement learning in robotics: A survey
International Journal of Robotics Research
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Rough terrain autonomous navigation continues to pose a challenge to the robotics community. Robust navigation by a mobile robot depends not only on the individual performance of perception and planning systems, but on how well these systems are coupled. When traversing complex unstructured terrain, this coupling (in the form of a cost function) has a large impact on robot behavior and performance, necessitating a robust design. This paper explores the application of Learning from Demonstration to this task for the Crusher autonomous navigation platform. Using expert examples of desired navigation behavior, mappings from both online and offline perceptual data to planning costs are learned. Challenges in adapting existing techniques to complex online planning systems and imperfect demonstration are addressed, along with additional practical considerations. The benefits to autonomous performance of this approach are examined, as well as the decrease in necessary designer effort. Experimental results are presented from autonomous traverses through complex natural environments.