Simultaneous localization and mapping (SLAM) is a fundamental technique block in the
indoor-navigation system for most autonomous vehicles and robots. SLAM aims at building …

Autonomous vehicle navigation is challenging since various types of road scenarios in real
urban environments have to be considered, particularly when only perception sensors are …

This paper aims at realizing an automatic parking method through a bird's eye view vision
system. With this method, vehicles can make robust and real-time detection and recognition …

Autonomous and intelligent vehicles will undoubtedly depend on an accurate ego
localization solution. Global navigation satellite systems suffer from multipath propagation …

Data fusion is an important process in a variety of tasks in the intelligent transportation
systems field. Most existing data fusion methods rely on the assumption of conditional …

Over the past years, inverse perspective mapping has been successfully applied to several
problems in the field of Intelligent Transportation Systems. In brief, the method consists of …

This paper presents a cognition-inspired agnostic framework for building a map for Visual
Place Recognition. This framework draws inspiration from human-memorability, utilizes the …

The demand for autonomous vehicles is increasing gradually owing to their enormous
potential benefits. However, several challenges, such as vehicle localization, are involved in …

This paper describes a dynamical model-based method for the localization of road vehicles
using terrain data from the vehicle's onboard sensors. Road data are encoded using linear …

In the urban environment or under complex traffic situation, conventional localization
methods like GPS, dead reckoning or SLAM are not precise enough for autonomous driving …