Seyed Abbas Sadat

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We consider a group of autonomous robots which perform the classical task of transporting resources from a source to home. The robots use ant-like emergent trail following to navigate between home and source. When trails lie close together , spatial interference between robots navigating in opposite directions reduces overall system performance. This paper(More)
— We consider the classical task of transporting resources from source to home by a group of autonomous robots. The robots use ant-like trail following to navigate between home and source. This paper studies the effect on global performance of changing the field of view of each robot's trail-following sensor. It is shown that, under certain conditions, a(More)
In the context of large-population multi-objective robot foraging , we present a novel ant-inspired trail-following algorithm that is able to adaptively untangle multiple trails. The emergent result is often a set of short, non-intersecting trails that produce good system throughput due a good trade off between the dual goals of minimizing travel distance(More)
We present a multi-modal multi-robot interaction whereby a user can identify an individual or a group of robots using haptic stimuli, and name them using a voice command (e.g."<i>You two are green</i>"). Subsequent commands can be addressed to the same robot(s) by name (e.g. "<i>Green! Take off</i>!"). We demonstrate this as part of a real-world integrated(More)
We present an integrated human-robot interaction system that enables a user to select and command a team of two Unmanned Aerial Vehicles (UAV) using voice, touch, face engagement and hand gestures. This system integrates multiple human [multi]-robot interaction interfaces as well as a navigation and mapping algorithm in a coherent semi-realistic scenario.(More)
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