あきたいぬ/アキタイヌ's repositories
Obstacles-gridmap-occupancy
Obstacles-gridmap-occupancy
occ_grid_mapping
A simple implementation of occupancy grid mapping.
occupancy_grid_mapping
Here is the method to build a grid map and get rid of the laser distortion
plane_fit_ground_filter
点云分割论文2017 Fast segmentation of 3d point clouds: A paradigm on lidar data for autonomous vehicle applications
PointPillars_MultiHead_40FPS
A REAL-TIME 3D detection network [Pointpillars] compiled by CUDA/TensorRT/C++.
3D_Lidar_Objects_Perception_and_Track
使用3d激光雷达数据进行障碍物的聚类感知和跟踪，主要参照autoware.ai和跟踪算法(https://github.com/k0suke-murakami/object_tracking)
AB3DMOT
(IROS 2020, ECCVW 2020) Official Python Implementation for "3D Multi-Object Tracking: A Baseline and New Evaluation Metrics"
apollo
An open autonomous driving platform
Autoware-LKAS
Autoware with LKAS
CenterPointTensorRT
A trt version of CenterPoint model for Lidar Detection
conti_radar_driver
:blue_book: ROS driver for Continental ARS 408-21/404-21 automotive radar
depth_clustering
:taxi: Fast and robust clustering of point clouds generated with a Velodyne sensor.
grid_map
Universal grid map library for mobile robotic mapping
LidarRoadBoundaryDetection
An speed and accuracy tradeoff method for LiDAR-based road boundary detection method in structured environments
multiple-object-tracking-lidar
C++ implementation to Detect, track and classify multiple objects using LIDAR scans or point cloud
object_detection_tracking
object detection and tracking (velodyne LiDAR)
Open3D
Open3D: A Modern Library for 3D Data Processing
opendbc
democratize access to car decoder rings
openpilot
openpilot is an open source driver assistance system. openpilot performs the functions of Automated Lane Centering and Adaptive Cruise Control for over 150 supported car makes and models.
RL-Stock
📈 如何用深度强化学习自动炒股
SoTA-Point-Cloud
🔥Deep Learning for 3D Point Clouds (IEEE TPAMI, 2020)
tensorRT_Pro
C++ library based on tensorrt integration
YOLOX
YOLOX is a high-performance anchor-free YOLO, exceeding yolov3~v5 with MegEngine, ONNX, TensorRT, ncnn, and OpenVINO supported. Documentation: https://yolox.readthedocs.io/