A Cost-Effective Person-Following System for Assistive Unmanned Vehicles with Deep Learning at the Edge

Anna Boschi, Francesco Salvetti, Vittorio Mazzia, Marcello Chiaberge
2020 Machines  
The vital statistics of the last century highlight a sharp increment of the average age of the world population with a consequent growth of the number of older people. Service robotics applications have the potentiality to provide systems and tools to support the autonomous and self-sufficient older adults in their houses in everyday life, thereby avoiding the task of monitoring them with third parties. In this context, we propose a cost-effective modular solution to detect and follow a person
more » ... nd follow a person in an indoor, domestic environment. We exploited the latest advancements in deep learning optimization techniques, and we compared different neural network accelerators to provide a robust and flexible person-following system at the edge. Our proposed cost-effective and power-efficient solution is fully-integrable with pre-existing navigation stacks and creates the foundations for the development of fully-autonomous and self-contained service robotics applications.
doi:10.3390/machines8030049 fatcat:zekf3l44pzafhijtd3sq6hzjuy