Author name cluster

Stephen Se

Possible papers associated with this exact author name in Arrow. This page groups case-insensitive exact name matches and is not a full identity disambiguation profile.

6 papers

1 author row

ICRA Conference 2006 Conference Paper

Photo-realistic 3D Model Reconstruction

Stephen Se
Piotr Jasiobedzki

Photo-realistic 3D modeling is a challenging problem and has been a research topic for many years. Quick generation of photo-realistic three-dimensional calibrated models using a hand-held device is highly desirable for applications ranging from forensic investigation, mining, to mobile robotics. In this paper, we present the instant Scene Modeler (iSM), a 3D imaging system that automatically creates 3D models using an off-the-shelf hand-held stereo camera. The user points the camera at a scene of interest and the system will create a photo-realistic 3D calibrated model automatically within minutes. Field tests in various environments have been carried out with promising results

Details

IROS Conference 2002 Conference Paper

Global localization using distinctive visual features

Stephen Se
David G. Lowe
James J. Little

We have previously developed a mobile robot system which uses scale invariant visual landmarks to localize and simultaneously build a 3D map of the environment In this paper, we look at global localization, also known as the kidnapped robot problem, where the robot localizes itself globally, without any prior location estimate. This is achieved by matching distinctive landmarks in the current frame to a database map. A Hough transform approach and a random sample consensus (RANSAC) approach for global localization are compared, showing that RANSAC is much more efficient. Moreover, robust global localization can be achieved by matching a small sub-map of the local region built from multiple frames.

Details

IROS Conference 2002 Conference Paper

Vision-based mapping with backward correction

Stephen Se
David G. Lowe
James J. Little

We consider the problem of creating a consistent alignment of multiple 3D submaps containing distinctive visual landmarks in an unmodified environment. An efficient map alignment algorithm based on landmark specificity is proposed to align submaps. This is followed by a global minimization using the close-the-loop constraint. Landmark uncertainty is taken into account in the pairwise alignment and the global minimization process. Experiments show that the pairwise alignment of submaps with backward correction produces a consistent global 3D map. Our vision-based mapping approach using sparse 3D data is different from other existing approaches which use dense 2D range data from laser or sonar rangefinders.

Details

ICRA Conference 2002 Conference Paper

Waiting with José, a Vision-Based Mobile Robot

Pantelis Elinas
Jesse Hoey
Darrell Lahey
Jefferson D. Montgomery
Don Ray Murray
Stephen Se
James J. Little

Jose is a visually guided autonomous robotic waiter. He circulates around a room populated by groups of people, politely serving appetizers to humans. The serving task combines elements of robotics with human computer interaction, challenging control architecture with multiple task integration. This paper describes our purely vision-based approach to this task. Methods for mapping, localization and navigation are presented and discussed, including issues of safety for both robots and humans. Our work on human-robot interaction is covered, as well as our solutions to various tasks specific to serving food. We present results of our methods from sample experiments in our laboratory. We further discuss our experiences at the 2001 AAAI mobile robot "Hors D'oeuvres Anyone? " competition, at which Jose took first prize.

Details

IROS Conference 2001 Conference Paper

Local and global localization for mobile robots using visual landmarks

Stephen Se
David G. Lowe
James J. Little

Our mobile robot system uses scale-invariant visual landmarks to localize itself and build a 3D map of the environment simultaneously. As image features are not noise-free, we carry out error analysis and use Kalman filters to track the 3D landmarks, resulting in a database map with landmark positional uncertainty. By matching a set of landmarks as a whole, our robot can localize itself globally based on the database containing landmarks of sufficient distinctiveness. Experiments show that recognition of position within a map without any prior estimate can be achieved using the scale-invariant landmarks.

Details

ICRA Conference 2001 Conference Paper

Vision-based Mobile Robot Localization And Mapping using Scale-Invariant Features

Stephen Se
David G. Lowe
James J. Little

A key component of a mobile robot system is the ability to localize itself accurately and build a map of the environment simultaneously. In this paper, a vision-based mobile robot localization and mapping algorithm is described which uses scale-invariant image features as landmarks in unmodified dynamic environments. These 3D landmarks are localized and robot ego-motion is estimated by matching them, taking into account the feature viewpoint variation. With our Triclops stereo vision system, experiments show that these features are robustly matched between views, 3D landmarks are tracked, robot pose is estimated and a 3D map is built.

Details