Autonomous Driving in Unstructured Environments: How Far Have We Come?
Research on autonomous driving in unstructured outdoor environments is less advanced
than in structured urban settings due to challenges like environmental diversities and scene …
than in structured urban settings due to challenges like environmental diversities and scene …
Efficient and robust lidar-based end-to-end navigation
Deep learning has been used to demonstrate end-to-end neural network learning for
autonomous vehicle control from raw sensory input. While LiDAR sensors provide reliably …
autonomous vehicle control from raw sensory input. While LiDAR sensors provide reliably …
Autonomous navigation in inclement weather based on a localizing ground penetrating radar
Most autonomous driving solutions require some method of localization within their
environment. Typically, onboard sensors are used to localize the vehicle precisely in a …
environment. Typically, onboard sensors are used to localize the vehicle precisely in a …
Alt-pilot: Autonomous navigation with language augmented topometric maps
We present an autonomous navigation system that operates without assuming HD LiDAR
maps of the environment. Our system, ALT-Pilot, relies only on publicly available road …
maps of the environment. Our system, ALT-Pilot, relies only on publicly available road …
Vision‐Based Branch Road Detection for Intersection Navigation in Unstructured Environment Using Multi‐Task Network
Autonomous vehicles need a driving method to be less dependent on localization data to
navigate intersections in unstructured environments because these data may not be …
navigate intersections in unstructured environments because these data may not be …
Dark reciprocal-rank: Teacher-to-student knowledge transfer from self-localization model to graph-convolutional neural network
T Koji, T Kanji - … IEEE International Conference on Robotics and …, 2021 - ieeexplore.ieee.org
In visual robot self-localization, graph-based scene representation and matching have
recently attracted research interest as robust and discriminative methods for self-localization …
recently attracted research interest as robust and discriminative methods for self-localization …
Exploring navigation maps for learning-based motion prediction
J Schmidt, J Jordan, F Gritschneder… - … on Robotics and …, 2023 - ieeexplore.ieee.org
The prediction of surrounding agents' motion is a key for safe autonomous driving. In this
paper, we explore navigation maps as an alternative to the predominant High Definition …
paper, we explore navigation maps as an alternative to the predominant High Definition …
Road descriptors for fast global localization on rural roads using OpenStreetMap
S Ninan, S Rathinam - Sensors, 2023 - mdpi.com
Accurate pose estimation is a fundamental ability that all mobile robots must posses in order
to navigate a given environment. Much like a human, this ability is dependent on the robot's …
to navigate a given environment. Much like a human, this ability is dependent on the robot's …
[책][B] Traffic light detection and V2I communications of an autonomous vehicle with the traffic light for an effective intersection navigation using MAVS simulation
M Rahman - 2023 - search.proquest.com
Intersection Navigation plays a significant role in autonomous vehicle operation. This paper
focuses on enhancing autonomous vehicle intersection navigation through advanced …
focuses on enhancing autonomous vehicle intersection navigation through advanced …
Hierarchical road topology learning for urban mapless driving
The majority of current approaches in autonomous driving rely on High-Definition (HD) maps
which detail the road geometry and surrounding area. Yet, this reliance is one of the …
which detail the road geometry and surrounding area. Yet, this reliance is one of the …