A realistic benchmark for visual indoor place recognition
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We propose a new method for the localization of a Micro Aerial Vehicle (MAV) with respect to a ground robot. We solve the problem of registering the 3D maps computed by the robots using different sensors: a dense 3D reconstruction from the MAV monocular ca ...
We present an approach for distributed real-time recognition tasks using a swarm of mobile robots. We focus on the visual recognition of hand gestures, but the solutions that we provide have general applicability and address a number of challenges common t ...
This paper describes the robot vision track that has been proposed to the ImageCLEF 2010 participants. The track addressed the problem of visual place classification, with a special focus on generalization. Participants were asked to classify rooms and are ...
Localization and context interpretation are two key competences for mobile robot systems. Visual place recognition, as opposed to purely geometrical models, holds promise of higher flexibility and association of semantics to the model. Ideally, a place rec ...
The ability of building robust semantic space representations of environments is crucial for the development of truly autonomous robots. This task, inherently connected with cognition, is traditionally achieved by training the robot with a supervised learn ...
Automatic recognition of gestures using computer vision is important for many real-world applications such as sign language recognition and human-robot interaction (HRI). Our goal is a real-time hand gesture-based HRI interface for mobile robots. We use a ...
Miniature curved artificial compound eyes (CURVACE) represent a promising tool to assist in navigation of mobile robots. In particular, they feature ideal properties for minidrones to navigate safely in indoor environments due to its panoramic field of vie ...
Micro aerial vehicles (MAVs) are a rapidly growing area of research and development in robotics. For autonomous robot operations, localization has typically been calculated using GPS, external camera arrays, or onboard range or vision sensing. In cluttered ...
Localization and context interpretation are two key competences for mobile robot systems. Visual place recognition, as opposed to purely geometrical models, holds promise of higher flexibility and association of semantics to the model. Ideally, a place rec ...
We study a simple algorithm inspired by the Brazil nut effect for achieving segregation in a swarm of mobile robots. The algorithm lets each robot mimic a particle of a certain size and broadcast this information locally. The motion of each particle is con ...
