(Georgia Institute of Technology, 2009-08)
Pronobis, A.; Caputo, B.; Jensfelt, Patric; Christensen, Henrik I.
An important competence for a mobile robot system is the ability to localize and
perform context interpretation. This is required to perform basic navigation and to
facilitate local specific services. Recent advances in vision have made this modality
a viable alternative to the traditional range sensors and visual place recognition
algorithms emerged as a useful and widely applied tool for obtaining information
about robot’s position. Several place recognition methods have been proposed using
vision alone or combined with sonar and/or laser. This research calls for standard
benchmark datasets for development, evaluation and comparison of solutions. To
this end, this paper presents two carefully designed and annotated image databases
augmented with an experimental procedure and extensive baseline evaluation. The
databases were gathered in an uncontrolled indoor office environment using two
mobile robots and a standard camera. The acquisition spanned across a time range
of several months and different illumination and weather conditions. Thus, the
databases are very well suited for evaluating the robustness of algorithms with
respect to a broad range of variations, often occurring in real-world settings. We
thoroughly assessed the databases with a purely appearance-based place recognition method based on Support Vector Machines and two types of rich visual features
(global and local).
(Georgia Institute of Technology, 2007-01)
Xiong, Ning; Christensen, Henrik I.; Svensson, Per
Dealing with conflicting and target-specific requirements is an important
issue in multi-sensor and multi-target tracking. This paper aims to allocate sensing
resources among various targets in reaction to individual information requests. The
approach proposed is to introduce agents for every relevant target responsible for its
tracking. Such agents are expected to bargain with each other for a division of
resources. A bilateral negotiation model is established for resource allocation in two-target
tracking. The applications of agent negotiation to target covariance tuning are
illustrated together with simulation results presented. Moreover, we suggest a way of
organizing simultaneous one-to-one negotiations, making our negotiation model still
applicable in scenarios of tracking more than two targets.
(Georgia Institute of Technology, 2006-10)
Kryki, V.; Kragic, Danica; Christensen, Henrik I.
This paper addresses the issue of measurement errors in visual servoing. The error
characteristics of the vision based state estimation and the associated uncertainty of
the control are investigated. The major contribution is the analysis of the propagation
of image error through pose estimation and visual servoing control law. Using
the analysis, two classical visual servoing methods are evaluated: position-based and
2 1/2 D visual servoing. The evaluation offers a tool to build and analyze hybrid
control systems such as switching or partitioning control.