Integration of Kinect and Low-Cost GNSS for Outdoor Navigation

Abstract

ABSTRACT:Since its launch on the market, Microsoft Kinect sensor has represented a great revolution in the field of low cost navigation, especially for indoor robotic applications. In fact, this system is endowed with a depth camera, as well as a visual RGB camera, at a cost of about 200$. The characteristics and the potentiality of the Kinect sensor have been widely studied for indoor applications. The second generation of this sensor has been announced to be capable of acquiring data even outdoors, under direct sunlight. The task of navigating passing from an indoor to an outdoor environment (and vice versa) is very demanding because the sensors that work properly in one environment are typically unsuitable in the other one. In this sense the Kinect could represent an interesting device allowing bridging the navigation solution between outdoor and indoor. In this work the accuracy and the field of application of the new generation of Kinect sensor have been tested outdoor, considering different lighting conditions and the reflective properties of the emitted ray on different materials. Moreover, an integrated system with a low cost GNSS receiver has been studied, with the aim of taking advantage of the GNSS positioning when the satellite visibility conditions are good enough. A kinematic test has been performed outdoor by using a Kinect sensor and a GNSS receiver and it is here presented.

GNSS/INS/LiDAR-SLAM Integrated Navigation System Based on Graph Optimization

“…In addition, for the low-cost MEMS (Micro-Electro-Mechanical System)-Inertial Measurement Unit (IMU), the navigation errors will accumulate and increase rapidly over time. In the context of low-cost integrated systems, image-based methodologies have also been explored, aiming at investigating the impact of drifts and errors experienced with such techniques, like in [2,3]. In the field of computer vision and robotics, Simultaneous Localization and Mapping (SLAM) technology is widely used for navigation in unfamiliar environments.…”