Embedded Multisensor System for Safe Point-to-Point Navigation of Impaired Users

Abstract

New smart objects to improve the quality of life in the ambient assisted living (AAL) scenario are capturing the interest of researchers and companies. In particular, novel assistive technologies are being developed to make accessible street navigation to impaired people. The solution that we propose in this new application domain of intelligent transportation systems is a framework for a safe point-to-point navigation, owing to high-detailed road graphs, including sidewalks, crosswalks, and generic “obstacles.” The system is based on a low-cost modular sensor box (embedded hardware) interfaced with a mobile/phone application that acts as an intelligent navigator. The main novelty is the capability to sense the surrounding area while being able to perform a fast path replanning, owing to a real-time link to a remote server, if an obstacle is detected. The sensing is performed using different sensors, such as ultrasound, lidar, and a 77-GHz mid-range automotive radar (absolutely novel in the AAL context), which are processed and fused in the well-established robot operating system (ROS). We tested the framework by analyzing its performance in two different configurations and environments by using, respectively, a sonar and a laser rangefinder in a building scenario and a radar in an urban environment. Even if in both cases results demonstrated a quite good robustness in the obstacle detection with a quasi-real-time route replanning, we were mainly interested and succeeded in demonstrating the high flexibility and extensibility of our framework.