5 accepted papers
Unmanned aerial vehicles are rapidly gaining popularity in many environmental monitoring tasks. A prerequisite for their autonomous operation is the ability to perform efficient and accurate mapping online, given limited on-board resources constraining operation time and computational capacity. To a
In this letter, we present a novel approach for predicting pedestrian crowd dynamics over longer time horizons (30 s). In dense environments over long time horizons, the number of pedestrian interactions is high, leading to the degradation of traditional pedestrian trajectory estimation techniques.
A predictive model for mobility systems capable of understanding the trajectory a user intends to follow in the environment is proposed. Understanding user intention is paramount for any shared-control navigation strategy between a user and an active robotic agent. Equally important however is being…
A multi-modal framework to generate user intention distributions when operating a mobile vehicle is proposed in this work. The model learns from past observed trajectories and leverages traversability information derived from the visual surroundings to produce a set of future trajectories, suitable…
In this paper, we present a novel approach that predicts spatially and temporally crowd behaviour for robotic social navigation. Integrating mobile robots into human society involves the fundamental problem of navigation in crowds. A robot should attempt to navigate in a way that is minimally invasi…