Model-based control of a robot manipulator
Model-based control of a robot manipulator
Artificial Intelligence Review - Special issue on lazy learning
Robot Learning From Demonstration
ICML '97 Proceedings of the Fourteenth International Conference on Machine Learning
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
Using inaccurate models in reinforcement learning
ICML '06 Proceedings of the 23rd international conference on Machine learning
ICML '06 Proceedings of the 23rd international conference on Machine learning
Analysis of sibling time series data: alignment and difference detection
Analysis of sibling time series data: alignment and difference detection
Learning for control from multiple demonstrations
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Bayesian inverse reinforcement learning
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Context-specific independence in Bayesian networks
UAI'96 Proceedings of the Twelfth international conference on Uncertainty in artificial intelligence
On Learning, Representing, and Generalizing a Task in a Humanoid Robot
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Learning for control from multiple demonstrations
Proceedings of the 25th international conference on Machine learning
Apprenticeship learning for helicopter control
Communications of the ACM - Barbara Liskov: ACM's A.M. Turing Award Winner
An Active Approach to Automatic Case Generation
ICCBR '09 Proceedings of the 8th International Conference on Case-Based Reasoning: Case-Based Reasoning Research and Development
Robustness analysis of evolutionary controller tuning using real systems
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
Comparing apples and oranges through partial orders: an empirical approach
ACC'09 Proceedings of the 2009 conference on American Control Conference
Towards a navigation system for autonomous indoor flying
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
Autonomous indoor helicopter flight using a single onboard camera
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Autonomous vehicle coordination with wireless sensor and actuator networks
ACM Transactions on Autonomous and Adaptive Systems (TAAS)
Autonomous Helicopter Aerobatics through Apprenticeship Learning
International Journal of Robotics Research
Learning GP-BayesFilters via Gaussian process latent variable models
Autonomous Robots
Learning Non-linear Multivariate Dynamics of Motion in Robotic Manipulators
International Journal of Robotics Research
Creation of DEVS models using imitation learning
Proceedings of the 2010 Summer Computer Simulation Conference
Genetic algorithm for induction of finite automata with continuous and discrete output actions
Proceedings of the 13th annual conference companion on Genetic and evolutionary computation
Fuzzy Logic Controller for a Mini Coaxial Indoor Helicopter
Journal of Intelligent and Robotic Systems
On combining decisions from multiple expert imitators for performance
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume One
Bayesian multitask inverse reinforcement learning
EWRL'11 Proceedings of the 9th European conference on Recent Advances in Reinforcement Learning
SUM'12 Proceedings of the 6th international conference on Scalable Uncertainty Management
Journal of Computer and Systems Sciences International
Scenario Trees and Policy Selection for Multistage Stochastic Programming Using Machine Learning
INFORMS Journal on Computing
Prediction from expert demonstrations for safe tele-surgery
International Journal of Automation and Computing
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We consider the problem of learning to follow a desired trajectory when given a small number of demonstrations from a sub-optimal expert. We present an algorithm that (i) extracts the---initially unknown---desired trajectory from the sub-optimal expert's demonstrations and (ii) learns a local model suitable for control along the learned trajectory. We apply our algorithm to the problem of autonomous helicopter flight. In all cases, the autonomous helicopter's performance exceeds that of our expert helicopter pilot's demonstrations. Even stronger, our results significantly extend the state-of-the-art in autonomous helicopter aerobatics. In particular, our results include the first autonomous tic-tocs, loops and hurricane, vastly superior performance on previously performed aerobatic maneuvers (such as in-place flips and rolls), and a complete airshow, which requires autonomous transitions between these and various other maneuvers.