A review of common techniques for visual simultaneous localization and mapping
Y Dai, J Wu, D Wang - Journal of Robotics, 2023 - Wiley Online Library
Mobile robots are widely used in medicine, agriculture, home furnishing, and industry.
Simultaneous localization and mapping (SLAM) is the working basis of mobile robots, so it is …
Simultaneous localization and mapping (SLAM) is the working basis of mobile robots, so it is …
Self-supervised monocular depth estimation with self-perceptual anomaly handling
It is attractive to extract plausible 3-D information from a single 2-D image, and self-
supervised learning has shown impressive potential in this field. However, when only …
supervised learning has shown impressive potential in this field. However, when only …
Neslam: Neural implicit mapping and self-supervised feature tracking with depth completion and denoising
In recent years, there have been significant advancements in 3D reconstruction and dense
RGB-D SLAM systems. One notable development is the application of Neural Radiance …
RGB-D SLAM systems. One notable development is the application of Neural Radiance …
Computer stereo vision for autonomous driving
As an important component of autonomous systems, autonomous car perception has had a
big leap with recent advances in parallel computing architectures. With the use of tiny but full …
big leap with recent advances in parallel computing architectures. With the use of tiny but full …
Computationally relaxed unscented kalman filter
Advanced robotics and autonomous vehicles rely on filtering and sensor fusion techniques
to a large extent. These mobile applications need to handle the computations onboard at …
to a large extent. These mobile applications need to handle the computations onboard at …
Onboard sensors-based self-localization for autonomous vehicle with hierarchical map
Localization is a fundamental and crucial module for autonomous vehicles. Most of the
existing localization methodologies, such as signal-dependent methods (RTK-GPS and …
existing localization methodologies, such as signal-dependent methods (RTK-GPS and …
Going beyond RF: A survey on how AI-enabled multimodal beamforming will shape the NextG standard
Incorporating artificial intelligence and machine learning (AI/ML) methods within the 5G
wireless standard promises autonomous network behavior and ultra-low-latency …
wireless standard promises autonomous network behavior and ultra-low-latency …
Computer stereo vision for autonomous driving: Theory and algorithms
As an important component of autonomous systems, autonomous car perception has had a
big leap with recent advances in parallel computing architectures. With the use of tiny but full …
big leap with recent advances in parallel computing architectures. With the use of tiny but full …
Computer-aided road inspection: Systems and algorithms
Road damage is an inconvenience and a safety hazard, severely affecting vehicle condition,
driving comfort, and traffic safety. The traditional manual visual road inspection process is …
driving comfort, and traffic safety. The traditional manual visual road inspection process is …
Long-awaited next-generation road damage detection and localization system is finally here
With the ever-increasing emphasis on road maintenance to a high standard, the need for
automated and robust road damage inspection (detection and localization) systems is …
automated and robust road damage inspection (detection and localization) systems is …