Perception and Action in Robotics

National DPI Projects PAU (2009-2011) and PAU+ (2012-2014)

SLAM - Simultaneous Localization and Mapping

Complete list of publications

Highlighted Publications

Planning reliable paths with Pose SLAM
R. Valencia, M. Morta, J. Andrade-Cetto and J.M. Porta.
IEEE Transactions on Robotics, 29(4): 1050-1059, 2013.
Show Abstract

In this paper we argue that Pose SLAM graphs can be directly used as belief roadmaps, and present a method that devises optimal navigation strategies by searching for the path in the pose graph with lowest accumulated robot pose uncertainty, independently of the map reference frame. The method shows improved navigation results when compared to shortest paths both over synthetic data and real datasets.

Action selection for single-camera SLAM.
T. Vidal-Calleja, A. Sanfeliu and J. Andrade-Cetto.
IEEE Transactions on Systems, Man and Cybernetics: Part B, 40(6): 1567-1581, 2010.
Show Abstract

A method for evaluating, at video rate, the quality of actions for a single camera while mapping unknown indoor environments is presented. The strategy maximizes mutual information between measurements and states to help the camera avoid making ill-conditioned measurements that are appropriate to lack of depth in monocular vision systems.

Amortized constant time state estimation in Pose SLAM and hierarchical SLAM using a mixed Kalman-information filter.
V. Ila, J.M. Porta, and J. Andrade-Cetto.
Robotics and Autonomous Systems, 59(5):310-318, 2011.
Show Abstract

The computational bottleneck in information-based SLAM is state mean and covariance recovery. In this paper we present a method to state estimation that is linear both in execution time and memory footprint at loop closure, and constant otherwise.

Information-based compact Pose SLAM.
V. Ila, J.M. Porta and J. Andrade-Cetto.
IEEE Transactions on Robotics, 26(1): 78-93, 2010.
Show Abstract,

This paper offers principled solutions to reduce the state size and the number of loop closures in Pose SLAM by considering only nonredundant poses and informative links.
The method also includes a tree-based technique to search for neighboring poses that scales logarithmically with the number of states.

code, documentation