SLAM Meets NeRF: A Survey of Implicit SLAM Methods
In recent years, Simultaneous Localization and Mapping (SLAM) systems have shown
significant performance, accuracy, and efficiency gains, especially when Neural Radiance …
significant performance, accuracy, and efficiency gains, especially when Neural Radiance …
Pin-slam: Lidar slam using a point-based implicit neural representation for achieving global map consistency
Accurate and robust localization and mapping are essential components for most
autonomous robots. In this paper, we propose a SLAM system for building globally …
autonomous robots. In this paper, we propose a SLAM system for building globally …
Outram: One-shot global localization via triangulated scene graph and global outlier pruning
One-shot LiDAR localization refers to the ability to estimate the robot pose from one single
point cloud, which yields significant advantages in initialization and relocalization …
point cloud, which yields significant advantages in initialization and relocalization …
3D LiDAR Mapping in Dynamic Environments Using a 4D Implicit Neural Representation
Building accurate maps is a key building block to enable reliable localization planning and
navigation of autonomous vehicles. We propose a novel approach for building accurate 3D …
navigation of autonomous vehicles. We propose a novel approach for building accurate 3D …
PC-NeRF: Parent-Child Neural Radiance Fields under Partial Sensor Data Loss in Autonomous Driving Environments
Reconstructing large-scale 3D scenes is essential for autonomous vehicles, especially
when partial sensor data is lost. Although the recently developed neural radiance fields …
when partial sensor data is lost. Although the recently developed neural radiance fields …
N-Mapping: Normal Guided Neural Non-Projective Signed Distance Fields for Large-scale 3D Mapping
Accurate and dense mapping in large-scale environments is essential for various robot
applications. Recently, implicit neural signed distance fields (SDFs) have shown promising …
applications. Recently, implicit neural signed distance fields (SDFs) have shown promising …
DeepMIF: Deep Monotonic Implicit Fields for Large-Scale LiDAR 3D Mapping
Recently, significant progress has been achieved in sensing real large-scale outdoor 3D
environments, particularly by using modern acquisition equipment such as LiDAR sensors …
environments, particularly by using modern acquisition equipment such as LiDAR sensors …
CCNDF: Curvature Constrained Neural Distance Fields from 3D LiDAR Sequences
Neural distance fields (NDF) have emerged as a powerful tool for solving 3D computer
vision and robotics downstream problems. While significant progress has been made in …
vision and robotics downstream problems. While significant progress has been made in …
TNDF-Fusion: Implicit Truncated Neural Distance Field for LiDAR Dense Mapping and Localization in Large Urban Environments
Large-scale 3D mapping is an important task for robotics and autonomous driving. However,
mobile robots and autonomous vehicles with limited hardware resources may face issues …
mobile robots and autonomous vehicles with limited hardware resources may face issues …
MoMo: Mouse-Based Motion Planning for Optimized Grasping to Declutter Objects Using a Mobile Robotic Manipulator
SK Jagatheesaperumal, VP Rajamohan… - Mathematics, 2023 - mdpi.com
The aim of this study is to develop a cost-effective and efficient mobile robotic manipulator
designed for decluttering objects in both domestic and industrial settings. To accomplish this …
designed for decluttering objects in both domestic and industrial settings. To accomplish this …