Approaching Behaviour Monitor and Vibration Indication in Developing a General Moving Object Alarm System (GMOAS)

Abstract

People who suffer from hearing impairment caused by illness, age or extremely noisy environments are constantly in danger of being hit or knocked down by fast moving objects behind them when they have no companion or augmented sensory system to warn them. In this paper, we propose the General Moving Object Alarm System (GMOAS), a system focused on aiding the safe mobility of people under these circumstances. The GMOAS is a wearable haptic device that consists of two main subsystems: (i) a moving object monitoring subsystem that uses laser range data to detect and track approaching objects, and (ii) an alarm subsystem that warns the user of possibly dangerous approaching objects by triggering tactile vibrations on an “alarm necklace”. For moving object monitoring, we propose a simple yet efficient solution to monitor the approaching behavior of objects. Compared with previous work in motion detection and tracking, we are not interested in specific objects but any type of approaching object that might harm the user. To this extent, we define a boundary in the laser range data where the objects are monitored. Within this boundary a fan-shape grid is constructed to obtain an evenly distributed spatial partitioning of the data. These partitions are efficiently clustered into continuous objects which are then tracked through time using an object association algorithm based on updating a deviation matrix that represents angle, distance and size variations of the objects. The speed of the tracked objects is monitored throughout the algorithm. When the speed of an approaching object surpasses the safety threshold, the alarm necklace is triggered indicating the approaching direction of the fast moving object. The alarm necklace is equipped with three motors that can indicate five directions with respect to the user: left, back, right, left-back and right-back. We performed three types of outdoor experiments (object passing, approaching and crossing) that empirically verified the effectiveness of our proposed algorithm. Furthermore, we analyzed the time and direction response based on neck vibrations. The statistical analysis (including hypothesis test) suggests that the chosen alarm necklace can provide a rapid indication for a quick human response.