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It can be noticed that the visibility relation is a binary relation when considering points, but a ternary relation when considering sets. The partially-visible space corresponds classically to the twilight (compared to the light (visible space) and the shade (non-visible space)). Figure 1.3 presents an example of visible, non-visible and partially-visible spaces.

International audience; The aim of the Cart-O-matic project was to design and build a multi-robot system able to autonomously map an unknown building. This work has been done in the framework of a French robotics contest called Defi CAROTTE organized by the General Delegation for Armaments (DGA) and the French National Research Agency (ANR). The scientific issues of this project deal with Simultaneous Localization And Mapping (SLAM), multi-robot collaboration and object recognition. In this paper, we will mainly focussed on the two first topics : after a general introduction, we will briefly describe the innovative simultaneous localization and mapping algorithm used during the competition. We will next explain how this algorithm can deal with multi-robots systems and 3D mapping. The next part of the paper will be dedicated to the multi-robot pathplanning and exploration strategy. The last section will illustrate the results with 2D and 3D maps, collaborative exploration strategies and example of planned trajectories.

International audience

Visibility is studied and used in several fields: computer graphics, telecommunication, robotics... For instance, in Computer-aided design (CAD) synthesis images are created by simulating light propagation in a scene. Visibility notions are then necessary to compute the visible objects from a point of view, and the shadow of those objects. In mobile robotics the visibility is used for path planning (visibility graph) and localization problems. This presentation is about visibility information for mobile robot localization. The objective is twofold. First a visibility notion based on segment intersections is presented. By considering a set-membership approach it is possible to develop contractors associated to this visibility relation. Then two applications of those visibility contractors to mobile robot localization are presented. The first one corresponds to the pose tracking of a team of robots. The idea is to use a Boolean information (the visibility between two robots: two robots are visible or not) in order to avoid the drifting of those robots (in order to maintain the precision of their position estimations). The second application corresponds to the processing of an original constraint for a set-membership global localization algorithm. This global localization algorithm is based on a CSP approach (Constraint Satisfaction Problem). Adding a visibility constraint to this CSP improves the accuracy of the algorithm.

International audience; This paper proposes a set-membership method based on interval analysis to solve the pose tracking problem. The originality of this approach is to consider weak sensors data: the visibility between two robots. By using a team of robots and this boolean information (two robots see each other or not), the objective is to compensate the odometry errors and be able to localize, in a guaranteed way, the robots in an indoor environment. This environment is supposed to be defined by two sets, an inner and an outer characterizations. Simulated results allow to evaluate the efficiency and the limits of the proposed method.

International audience; This paper presents a set membership method to deal with the kidnapping problem in mobile robotics. By using a range sensor, the odometry and a discrete map of an indoor environment, a robot has to detect a kidnapping situation, while performing a pose tracking, and then perform a global localization to estimate its new pose (position and orientation). In a bounded error context the IAL (Interval Analysis Localization) algorithm searches a small box (interval vector) that includes the robot's pose, using interval analysis and constraint propagation tools. This algorithm allows to perform a pose tracking and a global localization. Using this algorithm, it is possible to deal with the kidnapping problem. This method is tested using real data, recorded during the CAROTTE challenge, organized by the French ANR (National Research Agency) and the French Army. As it is shown in this paper with the IAL algorithm, interval analysis is an efficient tool to solve the kidnapping problem.

International audience