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Object Classification in Robotic Swarms

The ability to identify the target of a common action is fundamental for the development of a multi-robot swarm able to interact with the environment. In most existing systems, the identification is carried on individually, based on either color coding, shape or complex vision systems. Those methods usually assume a broad point of view over the objects, which are observed in their entirety. This assumption is sometimes difficult to fulfill in practice, and in particular in swarm systems, constituted by a multitude of small robots with limited sensing and computational capabilities.

Vegetation Identification via Online Spectral Analysis

The knowledge of the spectral signatures of different materials is used in remote sensing to classify objects sensed with spectral cameras. This information can be useful onboard of robots in order to identify materials and use this information to identify and classify surrounding objects. However, reflectance sensors are usually expensive and heavy, so unsuitable for their equipment on Micro Aerial Vehicles (MAV). Some principles of remote sensing can nevertheless be applied onboard by developing a camera array in which each camera collects images at specific wavelengths of interest.

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