Thrun, Sebastian 1967-
Most widely held works by Sebastian Thrun
Probabilistic robotics by Sebastian Thrun ( Book )
10 editions published between 2005 and 2010 in English and held by 350 libraries worldwide
Probablistic robotics is a growing area in the subject, concerned with perception and control in the face of uncertainty and giving robots a level of robustness in real-world situations. This book introduces techniques and algorithms in the field.
FastSLAM a scalable method for the simultaneous localization and mapping problem in robotics by Michael Montemerlo ( Book )
10 editions published in 2007 in English and held by 293 libraries worldwide
This monograph describes a new family of algorithms for the simultaneous localization and mapping problem in robotics (SLAM). SLAM addresses the problem of acquiring an environment map with a roving robot, while simultaneously localizing the robot relative to this map. This problem has received enormous attention in the robotics community, reaching a peak of popularity on the occasion of the DARPA Grand Challenge in October 2005, which was won by the team headed by the authors. The FastSLAM family of algorithms applies particle filters to the SLAM Problem, which provides new insights into the data association problem that is paramount in SLAM. The FastSLAM-type algorithms have enabled robots to acquire maps of unprecedented size and accuracy in a number of robot application domains and have been successfully applied in different dynamic environments, including the solution to the problem of people tracking.
Robotics research results of the 12th International Symposium ISRR by International Symposium on Robotics Research ( Book )
4 editions published in 2007 in English and held by 251 libraries worldwide
Explanation-based neural network learning : a lifelong learning approach by Sebastian Thrun ( Book )
7 editions published between 1995 and 1996 in 3 languages and held by 155 libraries worldwide
Robotics: science and systems I by Robotics: Science and Systems Conference ( Book )
2 editions published in 2005 in English and held by 141 libraries worldwide
Learning to learn ( Book )
1 edition published in 1998 in English and held by 139 libraries worldwide
Recent advances in robot learning ( Book )
1 edition published in 1996 in English and held by 72 libraries worldwide
Advances in neural information processing systems 16 : proceedings of the 2003 conference by Conference on Neural Information Processing Systems ( Book )
2 editions published in 2004 in English and held by 36 libraries worldwide
Advances in neural information processing systems. 15 Proceedings of the 2002 Neural Information Processing Systems Conference by Conference on Neural Information Processing Systems ( Book )
1 edition published in 2003 in English and held by 34 libraries worldwide
Field and Service Robotics (vol. # 24) Recent Advances in Research and Applications by S Yuta ( Book )
3 editions published in 2006 in English and held by 25 libraries worldwide
Robotics Research Results of the 12th International Symposium ISRR by Sebastian Thrun ( Book )
4 editions published in 2007 in English and held by 22 libraries worldwide
Robotics research : results of the 12th international symposium ISRR ( Book )
4 editions published in 2007 in English and held by 21 libraries worldwide
FastSLAM a Scalable Method for the Simultaneous Localization and Mapping Problem in Robotics ( Book )
1 edition published in 2007 in English and held by 10 libraries worldwide
Robotics : science and systems 1 ( Book )
5 editions published in 2005 in English and held by 7 libraries worldwide
A general feed-forward algorithm for gradient descent in connectionist networks by Sebastian Thrun ( Book )
2 editions published in 1990 in German and English and held by 6 libraries worldwide
Abstract: "An extended feed-forward algorithm for recurrent connectionist networks is presented. This algorithm, which works locally in time, is derived both for discrete-in-time networks and for continuous networks. Several standard gradient descent algorithms for connectionist networks (e.g. , , , , ), especially the backpropagation algorithm , are mathematically derived as a special case of this general algorithm. The learning algorithm presented in this paper is a superset of gradient descent learning algorithms for multilayer networks, recurrent networks and time-delay networks that allows any combinations of their components.
On planning and exploration in non-discrete environments by Sebastian B Thrun ( Book )
2 editions published in 1991 in German and English and held by 6 libraries worldwide
Abstract: "The application of reinforcement learning to control problems has received considerable attention in the last few years [And86, Bar89, Sut84]. In general there are two principles to solve reinforcement learning problems: direct and indirect techniques, both having their advantages and disadvantages. We present a system that combines both methods [TML91, TML90]. By interaction with an unknown environment a world model is progressively constructed using the backpropagation algorithm. For optimizing actions with respect to future reinforcement planning is applied in two steps: An experience network proposes a plan which is subsequently optimized by gradient descent with a chain of model networks.
Efficient exploration in reinforcement learning by Sebastian B Thrun ( Book )
1 edition published in 1992 in English and held by 6 libraries worldwide
Abstract: "Exploration plays a fundamental role in any active learning system. This study evaluates the role of exploration in active learning and describes several local techniques for exploration in finite, discrete domains, embedded in a reinforcement learning framework (delayed reinforcement). This paper distinguishes between two families of exploration schemes: undirected and directed exploration. While the former family is closely related to random walk exploration, directed exploration techniques memorize exploration-specific knowledge which is used for guiding the exploration search.
The MONK's problems : a performance comparison of different learning algorithms ( Book )
1 edition published in 1991 in English and held by 6 libraries worldwide
Abstract: "This report summarizes a comparison of different learning techniques which was performed at the 2nd European Summer School on Machine Learning, held in Belgium during summer 1991. A variety of symbolic and non-symbolic learning techniques -- namely AQ17-DCI, AQ17-HCI, AQ17-FCLS, AQ14-NT, AQ15-GA, Assistant Professional, mFOIL, ID5R, IDL, ID5R-hat, TDIDT, ID3, AQR, CN2, CLASS-WEB, ECOBWEB, PRISM, Backpropagation, and Cascade Correlation -- are compared on three classification problems, the MONK's problems. The MONK's problems are derived from a domain in which each training example is represented by six discrete-valued attributes. Each problem involves learning a binary function defined over this domain, from a sample of training examples of this function.
Lifelong learning : a case study by Sebastian B Thrun ( Book )
1 edition published in 1995 in English and held by 5 libraries worldwide
Abstract: "Machine learning has not yet succeeded in the design of robust learning algorithms that generalize well from very small datasets. In contrast, humans often generalize correctly from only a single training example, even if the number of potentially relevant features is large. To do so, they successfully exploit knowledge acquired in previous learning tasks, to bias subsequent learning. This paper investigates learning in a lifelong context. Lifelong learning addresses situations where a learner faces a stream of learning tasks. Such scenarios provide the opportunity for synergetic effects that arise if knowledge is transferred across multiple learning tasks. To study the utility of transfer, several approaches to lifelong learning are proposed and evaluated in an object recognition domain. It is shown that all these algorithms generalize consistently more accurately from scarce training data than comparable 'single-task' approaches."
Learning one more thing by Sebastian B Thrun ( Book )
1 edition published in 1994 in English and held by 5 libraries worldwide
Abstract: "Most research on machine learning has focused on scenarios in which a learner faces a single, isolated learning task. The lifelong learning framework assumes instead that the learner encounters a multitude of related learning tasks over its lifetime, providing the opportunity for the transfer of knowledge. This paper studies lifelong learning in the context of binary classification. It presents the invariance approach, in which knowledge is transferred via a learned model of the invariances of the domain. Results on learning to recognize objects from color images demonstrate superior generalization capabilities if invariances are learned and used to bias subsequent learning."
Actuators Algorithms Artificial intelligence Automation Bayesian statistical decision theory Cartography Cluster analysis--Computer programs Computer networks Computer vision Conference proceedings Connection machines Data mining Data transmission systems Detectors Embedded computer systems--Programming Engineering Filters (Mathematics) Heuristic programming Image processing Kalman filtering Machine learning Mappings (Mathematics) Maps Markov processes Mobile robots Monte Carlo method Neural computers Neural networks (Computer science) Probabilistic automata Probabilities Reinforcement learning Resolution (Optics) Robot camera Robotics Robots--Control systems Robots--Motion Robots--Programming Sampling (Statistics) Statistics Structural control (Engineering) Theory of distributions (Functional analysis) Visual perception
Thrun, S. 1967-
Thrun, Sebastian B.
Thrun, Sebastian B. 1967-