NeuV SLAM

NeuV SLAM (Neural Voxel SLAM) focuses on creating accurate and efficient 3D maps of environments using neural networks to process sensor data, primarily RGB-D images. Current research emphasizes improving the speed and robustness of these systems, exploring architectures like Gaussian splatting and multiresolution voxel representations, and optimizing deep learning models for resource-constrained platforms. This work is significant for advancing robotics, autonomous navigation, and 3D scene reconstruction by enabling real-time mapping in dynamic environments and improving the accuracy and efficiency of existing methods.