- Autonomous Mapping and Navigation Using SLAM Toolbox, Nav2, Gazebo, and Rviz Visualization
- GLC: Semantic Graph-Guided Coarse-Fine-Refine Full Loop Closing for LiDAR SLAM
- Drift-free Visual SLAM using Digital Twins
- pySLAM: a visual SLAM pipeline in Python for monocular, stereo and RGBD cameras.
- pySLAM SLAM pipeline updates
- ICRA 2025 Gaussian-LIC: Real-Time Photo-Realistic SLAM with Gaussian Splatting and LiDAR-Inertial-Camera Fusion
- An unofficial open source implentation of CSIRO's Wildcat SLAM.
- DynoSAM: Dynamic Object Smoothing and Mapping for Dynamic SLAM
- [Present and Future of SLAM in Extreme Environments](https://ieeexplore.
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| %matplotlib inline | |
| import numpy as np | |
| from skimage.io import imshow | |
| from skimage.measure import label | |
| from scipy.ndimage.morphology import distance_transform_edt | |
| def generate_random_circles(n = 100, d = 256): | |
| circles = np.random.randint(0, d, (n, 3)) | |
| x = np.zeros((d, d), dtype=int) | |
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| import math | |
| import torch | |
| import torch.nn as nn | |
| import torch.nn.functional as F | |
| from torch.nn.modules.utils import _pair, _quadruple | |
| class MedianPool2d(nn.Module): | |
| """ Median pool (usable as median filter when stride=1) module. | |
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| # Required download | |
| # cudnn-8.0-linux-x64-v5.1.tgz | |
| curl -L -o cuda_8.0.44_linux.run https://developer.nvidia.com/compute/cuda/8.0/prod/local_installers/cuda_8.0.44_linux-run | |
| curl -L -O http://us.download.nvidia.com/XFree86/Linux-x86_64/367.27/NVIDIA-Linux-x86_64-367.27.run | |
| sudo apt-get install build-essential | |
| sudo apt-get install linux-image-extra-`uname -r` | |
| sudo sh cuda_8.0.44_linux.run | |
| echo -e "export CUDA_HOME=/usr/local/cuda\nexport PATH=\$PATH:\$CUDA_HOME/bin\nexport LD_LIBRARY_PATH=\$LD_LINKER_PATH:\$CUDA_HOME/lib64" >> ~/.bashrc |
- Curriculum Learning - When training machine learning models, start with easier subtasks and gradually increase the difficulty level of the tasks.
- Motivation comes from the observation that humans and animals seem to learn better when trained with a curriculum like a strategy.
- Link to the paper.