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apollo

An open autonomous driving platform

boustrophedoncellulardecompositionpathplanning

Complete Coverage Path Planning Using Boustrophedon Cellular Decomposition Algorithm

cppmaster

C++ Master Learning Roadmap, especially for AIoT and C++ advanced SWE

dig-into-apollo

Apollo notes (Apollo学习笔记) - Apollo learning notes for beginners.

efficient-motion-planning

To guarantee safe and efficient driving for automated vehicles in complicated traffic conditions, the motion planning module of automated vehicles are expected to generate collision-free driving policies as soon as possible in varying traffic environment. However, there always exist a tradeoff between efficiency and accuracy for the motion planning algorithms. Besides, most motion planning methods cannot find the desired trajectory under extreme scenarios (e.g., lane change in crowded traffic scenarios). This study proposed an efficient motion planning strategy for automated lane change based on Mixed-Integer Quadratic Optimization (MIQP) and Neural Networks. We modeled the lane change task as a mixed-integer quadratic optimization problem with logical constraints, which allows the planning module to generate feasible, safe and comfortable driving actions for lane changing process. Then, a hierarchical machine learning structure that consists of SVM-based classification layer and NN-based action learning layer is established to generate desired driving policies that can make online, fast and generalized motion planning. Our model is validated in crowded lane change scenarios through numerical simulations and results indicate that our model can provide optimal and efficient motion planning for automated vehicles

epsilon

grid_map

Universal grid map library for mobile robotic mapping

gridsearch

vehicle/robot planning based on grid search algorithm

grips

Gradient-Informed Path Smoothing for Wheeled Mobile Robots (GRIPS)

hybrid-a-star-annotation

Hybrid A*路径规划器的代码注释

hybrid-astar-planner

Hybrid A* Path Planner

kdtree

Simple C++ KD-Tree implementation

leastsquaremethod

mav_trajectory_generation

Polynomial trajectory generation and optimization, especially for rotary-wing MAVs.

mpl_ros

A ROS wrapper for trajectory planning based on motion primitives

octomap_ros

ROS package to provide conversion functions between ROS / PCL and OctoMap's native types.

papers

path_planner

Hybrid A* Path Planner for the KTH Research Concept Vehicle

path_smoother

smooth path/curve with Gradient Descent method

polygon_coverage_planning

Coverage planning in general polygons with holes.

pythonrobotics

Python sample codes for robotics algorithms.

reinforcement-learning-code

rpg_information_field

Information Field for Perception-aware Planning

smartcar

自动驾驶系统实现

teb_local_planner

An optimal trajectory planner considering distinctive topologies for mobile robots based on Timed-Elastic-Bands (ROS Package)