Project description

Description

We are developing a robot that can achieve autonomous semantic 3D mapping of a large unknown area. This objective is achieved by integrating two major sub-systems. The first sub-system provides 3D simultaneous localization and mapping relying on multiple laser sensors and panoramic vision. The map is based on a hierarchical representation integrating a textured 3D structure at the lowest level and higher-level semantic concepts such as rooms, corridors and objects detected in the environment. The second sub-system provides visual object search using a panoramic and an active camera. This sub-system integrates a panoramic visual saliency computation in order to rapidly select area where objects might be present and a higher-resolution appearance-based object detection and recognition method using a pan-tilt-zoom camera focused toward the salient regions in order to robustly detect objects. The mapping and the detection of objects is conducted autonomously through the use of a multi-objectives exploration strategy that includes the need for mapping 3D structure and the need for searching objects and semantic elements present in the environment.