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Abstract

In the context of stereovision SLAM, we propose a way to enrich the landmark models. Vision-based SLAM usually approaches rely on interest points associated to a point in the cartesian space : by adjoining oriented planar patches (if they are present in the environment), we augment the landmark description with an oriented frame. Thanks to this additional information, the robot pose is fully obser- vable with the perception of a single landmark, and the knowledge of the patches orientation helps the matching of landmarks perceived from two different viewpoints. The pa- per depicts the chosen landmark model, the way to extract and match them, and presents some SLAM results obtained with such landmarks.

Mots-Clés / Keywords

Abstract

In military missions in hostile environments involving teams of UAVs flying in formation, it is important to get the maximum benefits of the auto-protection systems of each aircraft to enhance the global security and efficiency of the team. One way to achieve this is to select a proper configuration for the formation. In this paper, we present an approach to autonomously adapt the configuration of a formation and we focus on its evaluation within a realistic framework where each UAV is simulated independently and communicate through a network.

Abstract

This paper presents a software component, the plan database, which provides the needed services to define plans, execute them and more importantly adapt them during execution. This plan database handles fully dynamic plans (insertion and removal of tasks), defines task transformation operators and provides tools for safe concurrent execution and modification of plans. These features are essential in multi- robot and human-robot contexts, where tasks need to be easily passed between systems and plan adaptation helps coping with the unpredictability inherent to systems where multiple agent make decisions.

Mots-Clés / Keywords

Abstract

This paper presents a software component, the plan database, which provides the needed services to define plans, execute them and more importantly adapt them during execution. This plan database handles fully dynamic plans (insertion and removal of tasks), defines task transformation operators and provides tools for safe concurrent execution and modification of plans. These features are essential in multi-robot and human-robot contexts, where tasks need to be easily passed between systems and plan adaptation helps coping with the unpredictability inherent to systems where multiple agent make decisions.

Mots-Clés / Keywords

Mots-Clés / Keywords

Abstract

Building a spatially consistent model is a key functionality to endow a mobile robot with autonomy. Without an initial map or an absolute localization means, it requires to concurrently solve the localization and mapping problems. For this purpose, vision is a powerful sensor, because it provides data from which stable features can be extracted and matched as the robot moves. But it does not directly provide 3D information, which is a difficulty for estimating the geometry of the environment. This article presents two approaches to the SLAM problem using vision: one with stereovision, and one with monocular images. Both approaches rely on a robust interest point matching algorithm that works in very diverse environments. The stereovision based approach is a classic SLAM implementation, whereas the monocular approach introduces a new way to initialize landmarks. Both approaches are analyzed and compared with extensive experimental results, with a rover and a blimp.