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Benchmarking neural radiance fields for autonomous robots: An overview
Abstract Neural Radiance Field (NeRF) has emerged as a powerful paradigm for scene
representation, offering high-fidelity renderings and reconstructions from a set of sparse and …
representation, offering high-fidelity renderings and reconstructions from a set of sparse and …
Fusionportablev2: A unified multi-sensor dataset for generalized slam across diverse platforms and scalable environments
MARS-LVIG dataset: A multi-sensor aerial robots SLAM dataset for LiDAR-visual-inertial-GNSS fusion
In recent years, advancements in Light Detection and Ranging (LiDAR) technology have
made 3D LiDAR sensors more compact, lightweight, and affordable. This progress has …
made 3D LiDAR sensors more compact, lightweight, and affordable. This progress has …
Loner: Lidar only neural representations for real-time slam
This letter proposes LONER, the first real-time LiDAR SLAM algorithm that uses a neural
implicit scene representation. Existing implicit map** methods for LiDAR show promising …
implicit scene representation. Existing implicit map** methods for LiDAR show promising …
Towards robust robot 3d perception in urban environments: The ut campus object dataset
We introduce the UT Campus Object Dataset (CODa), a mobile robot egocentric perception
dataset collected on the University of Texas Austin Campus. Our dataset contains 8.5 h of …
dataset collected on the University of Texas Austin Campus. Our dataset contains 8.5 h of …
ECMD: An event-centric multisensory driving dataset for SLAM
Leveraging multiple sensors enhances complex environmental perception and increases
resilience to varying luminance conditions and high-speed motion patterns, achieving …
resilience to varying luminance conditions and high-speed motion patterns, achieving …