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475-webcam-gauge-reading

475 Project - A CNN to read analog gauge readings in the lab

ad-rss-lib

Library implementing the Responsibility Sensitive Safety model (RSS) for Autonomous Vehicles

apollo-5.0

Fork of Apollo 5.0 for LGSVL Simulator

apollo_ros_bridge

Bridge messaging between Apollo and ROS

aruco-markers-pose-estimation-generation-python

Estimating pose using ArUCo Markers

aruco_ekf_slam

ArUco-based EKF-SLAM.

bundlefusion

[Siggraph 2017] BundleFusion: Real-time Globally Consistent 3D Reconstruction using Online Surface Re-integration

cadrl_ros

ROS package for dynamic obstacle avoidance for ground robots trained with deep RL

cartographer

Cartographer is a system that provides real-time simultaneous localization and mapping (SLAM) in 2D and 3D across multiple platforms and sensor configurations.

cartographer_ros

Provides ROS integration for Cartographer.

centernet

Object detection, 3D detection, and pose estimation using center point detection:

chatpaper

Use ChatGPT to summarize the arXiv papers. 全流程加速科研，利用chatgpt进行论文总结+润色+审稿+审稿回复

chenyf-ros-project

这是陈勇飞自己整理的ros 工程，主要给建图和导航源码注释，学习，整理相关功能

chineseocr_lite

超轻量级中文ocr，支持竖排文字识别, 支持ncnn推理 , psenet(8.5M) + crnn(6.3M) + anglenet(1.5M) 总模型仅17M

code-of-learn-deep-learning-with-pytorch

深度学习入门之PyTorch

conda

Specifying a conda environment with `environment.yml`

darknet-ocr

darknet text detect and darknet cnn ocr

data

declutter-reconstruct

deeplearning_ai_books

deeplearning.ai（吴恩达老师的深度学习课程笔记及资源）

diff-so-fancy

Good-lookin' diffs. Actually… nah… The best-lookin' diffs. :tada:

dm-vio-dataset

dynamic-occupancy-grid-map

Implementation of A Random Finite Set Approach for Dynamic Occupancy Grid Maps with Real-Time Application

dynamicpathfollowingrobot

This project explores making a wireless automatic guided robot which does not require any kind of intrusive modifications to be made to the environment, apart from installing an overhead camera. Generally environments that make use of automatic guided vehicles (AGVs) have to plan the path(s) where the robots should go before installing the tracks, like magnetic strips or metal tracks; this is an investment even before using the robots. If any change to the path(s) is required to be made, then more cost is incurred. In this paper a four wheeled differential drive robot has been controlled wirelessly to follow paths drawn on a graphical user interface within a workspace of 1.8m by 1.4m. The robot is controlled by correcting its orientation through visual feedback from a camera. Error analysis was performed to investigate how well the robot followed the path drawn. The estimated error of the robot is within a few centimeters of the path and can be reduced by modifying various thresholds.

gcnv2_slam

Real-time SLAM system with deep features

git-flow-test

gitdemo

golearning

grid_map

Universal grid map library for mobile robotic mapping

hardware-sync-of-robosense-and-xsense-mti-300

Robosense雷达和Xsense MTI-300的硬件时间同步方案