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- Stefanie Tellex, Thomas Kollar, +4 authors Nicholas Roy
- AAAI
- 2011

This paper describes a new model for understanding natural language commands given to autonomous systems that perform navigation and mobile manipulation in semi-structured environments. Previous approaches have used models with fixed structure to infer the likelihood of a sequence of actions given the environment and the command. In contrast, our framework,… (More)

- Sertac Karaman, Matthew R. Walter, Alejandro Perez, Emilio Frazzoli, Seth J. Teller
- 2011 IEEE International Conference on Robotics…
- 2011

The Rapidly-exploring Random Tree (RRT) algorithm, based on incremental sampling, efficiently computes motion plans. Although the RRT algorithm quickly produces candidate feasible solutions, it tends to converge to a solution that is far from optimal. Practical applications favor “anytime” algorithms that quickly identify an initial feasible… (More)

- Matthew R. Walter, Ryan M. Eustice, John J. Leonard
- I. J. Robotics Res.
- 2007

Recent research concerning the Gaussian canonical form for Simultaneous Localization and Mapping (SLAM) has given rise to a handful of algorithms that attempt to solve the SLAM scalability problem for arbitrarily large environments. One such estimator that has received due attention is the Sparse Extended Information Filter (SEIF) by Thrun et al., which is… (More)

- Alexander Bahr, Matthew R. Walter, John J. Leonard
- 2009 IEEE International Conference on Robotics…
- 2009

In cooperative navigation, teams of mobile robots obtain range and/or angle measurements to each other and dead-reckoning information to help each other navigate more accurately. One typical approach is moving baseline navigation, in which multiple Autonomous Underwater Vehicles (AUVs) exchange range measurements using acoustic modems to perform mobile… (More)

- Ryan M. Eustice, Hanumant Singh, John J. Leonard, Matthew R. Walter, Robert Ballard
- Robotics: Science and Systems
- 2005

— This paper describes a vision-based, large-area, simultaneous localization and mapping (SLAM) algorithm that respects the low-overlap imagery constraints typical of underwater vehicles while exploiting the inertial sensor information that is routinely available on such platforms. We present a novel strategy for efficiently accessing and maintaining… (More)

- Edwin Olson, Matthew R. Walter, Seth J. Teller, John J. Leonard
- Robotics: Science and Systems
- 2005

— We present an algorithm for finding a single cluster of well-connected nodes in a graph. The general problem is NP-hard, but our algorithm produces an approximate solution in O(n 2) by considering the spectral properties of the graph's adjacency matrix. We show how this algorithm can be used to find sets of self-consistent hypotheses while rejecting… (More)

- John J. Leonard, Jonathan P. How, +25 authors Jonathan Williams
- J. Field Robotics
- 2008

This paper describes the architecture and implementation of an autonomous passenger vehicle designed to navigate using locally perceived information in preference to potentially inaccurate or incomplete map data. The vehicle architecture was designed to handle the original DARPA Urban Challenge requirements of perceiving and navigating a road network with… (More)

- Ryan M. Eustice, Hanumant Singh, John J. Leonard, Matthew R. Walter
- I. J. Robotics Res.
- 2006

- Stefanie Tellex, Thomas Kollar, +4 authors Nicholas Roy
- AI Magazine
- 2011

A s robots move out of the lab and into the real world, it is critical to develop ways for human users to easily and flexibly command them. Natural language dialogue is a compelling solution to this problem because the operator can flexibly express complex requirements, enabling interaction with the robot as if it were another human. In order to engage… (More)

- Ryan M. Eustice, Matthew R. Walter, John J. Leonard
- 2005 IEEE/RSJ International Conference on…
- 2005

Recently, there have been a number of variant simultaneous localization and mapping (SLAM) algorithms that have made substantial progress towards large-area scalability by parameterizing the SLAM posterior within the information (canonical/inverse covariance) form. Of these, probably the most well known and popular approach is the sparse extended… (More)