Autonomous driving vehicles require both a precise localization and map** solution in
different driving environment. In this context, Simultaneous Localization and Map** …

Simultaneous localization and map** (SLAM) is crucial for the progression of autonomous
systems, including autonomous driving, augmented reality (AR), and robotics. Traditionally …

The assumption of scene rigidity is typical in SLAM algorithms. Such a strong assumption
limits the use of most visual SLAM systems in populated real-world environments, which are …

Simultaneous localization and map** (SLAM), as one of the core prerequisite
technologies for intelligent mobile robots, has attracted much attention in recent years …

We propose a real-time depth edge based RGB-D SLAM system for dynamic environment.
Our visual odometry method is based on frame-to-keyframe registration, where only depth …

Dynamic environments are challenging for visual SLAM as moving objects can impair
camera pose tracking and cause corruptions to be integrated into the map. In this paper, we …

To overcome the travelling difficulty for the visually impaired group, this paper presents a
novel ETA (Electronic Travel Aids)-smart guiding device in the shape of a pair of eyeglasses …

In this paper, a simultaneous localization and map** (SLAM) method that eliminates the
influence of moving objects in dynamic environments is proposed. This method utilizes the …

The COVID-19 pandemic has affected many countries, posing a threat to human health and
safety, and putting tremendous pressure on the medical system. This paper proposes a …

We present ClusterVO, a stereo Visual Odometry which simultaneously clusters and
estimates the motion of both ego and surrounding rigid clusters/objects. Unlike previous …