A survey on active simultaneous localization and mapping: State of the art and new frontiers
Active simultaneous localization and mapping (SLAM) is the problem of planning and
controlling the motion of a robot to build the most accurate and complete model of the …
controlling the motion of a robot to build the most accurate and complete model of the …
Self-driving cars: A survey
We survey research on self-driving cars published in the literature focusing on autonomous
cars developed since the DARPA challenges, which are equipped with an autonomy system …
cars developed since the DARPA challenges, which are equipped with an autonomy system …
Kitti-360: A novel dataset and benchmarks for urban scene understanding in 2d and 3d
For the last few decades, several major subfields of artificial intelligence including computer
vision, graphics, and robotics have progressed largely independently from each other …
vision, graphics, and robotics have progressed largely independently from each other …
Hypersim: A photorealistic synthetic dataset for holistic indoor scene understanding
For many fundamental scene understanding tasks, it is difficult or impossible to obtain per-
pixel ground truth labels from real images. We address this challenge by introducing …
pixel ground truth labels from real images. We address this challenge by introducing …
RTAB‐Map as an open‐source lidar and visual simultaneous localization and mapping library for large‐scale and long‐term online operation
Distributed as an open‐source library since 2013, real‐time appearance‐based mapping
(RTAB‐Map) started as an appearance‐based loop closure detection approach with …
(RTAB‐Map) started as an appearance‐based loop closure detection approach with …
Sni-slam: Semantic neural implicit slam
We propose SNI-SLAM a semantic SLAM system utilizing neural implicit representation that
simultaneously performs accurate semantic mapping high-quality surface reconstruction and …
simultaneously performs accurate semantic mapping high-quality surface reconstruction and …
DS-SLAM: A semantic visual SLAM towards dynamic environments
Simultaneous Localization and Mapping (SLAM) is considered to be a fundamental
capability for intelligent mobile robots. Over the past decades, many impressed SLAM …
capability for intelligent mobile robots. Over the past decades, many impressed SLAM …
A comprehensive review of coverage path planning in robotics using classical and heuristic algorithms
CS Tan, R Mohd-Mokhtar, MR Arshad - IEEE Access, 2021 - ieeexplore.ieee.org
The small battery capacities of the mobile robot and the un-optimized planning efficiency of
the industrial robot bottlenecked the time efficiency and productivity rate of coverage tasks in …
the industrial robot bottlenecked the time efficiency and productivity rate of coverage tasks in …
Present and future of slam in extreme environments: The darpa subt challenge
This article surveys recent progress and discusses future opportunities for simultaneous
localization and mapping (SLAM) in extreme underground environments. SLAM in …
localization and mapping (SLAM) in extreme underground environments. SLAM in …
Unsupervised point cloud representation learning with deep neural networks: A survey
Point cloud data have been widely explored due to its superior accuracy and robustness
under various adverse situations. Meanwhile, deep neural networks (DNNs) have achieved …
under various adverse situations. Meanwhile, deep neural networks (DNNs) have achieved …