Autonomous Apartment Exploration, Modelling and Segmentation for Service Robotics

Guido Manfredi (1) , Sandra Devin (2) , Michel Devy (1) , Daniel Sidobre (2)

1 LAAS-RAP - Équipe Robotique, Action et Perception
2 LAAS-RIS - Équipe Robotique et InteractionS

This work proposes a full pipeline for a robot to explore, model and segment an apartment from a 2-D map. Viewpoints are found offline and then visited by the robot to create a 3-D model of the environment. This model is segmented in order to find the various rooms and how they are linked (windows, doors, walls) yielding a topological map. Moreover areas of interest are also segmented, in this case furniture's planar surfaces. The method is validated on a realistic three rooms apartment. Results show that, despite occlusion, autonomous exploration and modeling covers 95% of the apartment. For the segmentation part, 1 link out of 14 is wrongly classified while all the existing areas of interest are found. Fig. 1. The ADREAM apartment is used to illustrate the different algorithms and to perform the experiments described later. Note that the furniture visible in this view is slightly different from the real setup.

Mots clés: Autonomous; Exploration; Modeling; Segmentation; Service Robotics

Domaines: Vision par ordinateur et reconnaissance de formes [cs.CV]; Robotique [cs.RO]

Guido Manfredi, Sandra Devin, Michel Devy, Daniel Sidobre. Autonomous Apartment Exploration, Modelling and Segmentation for Service Robotics. IAV 2016 - 9th IFAC Symposium on Intelligent Autonomous Vehicles, Jun 2016, Leipzig, Germany. pp.120-125, ⟨10.1016/j.ifacol.2016.07.719⟩. ⟨hal-01355112⟩