Pinned Repositories
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
FleverX's Repositories
FleverX/GridSearch
vehicle/robot planning based on grid search algorithm
FleverX/apollo
An open autonomous driving platform
FleverX/BoustrophedonCellularDecompositionPathPlanning
Complete Coverage Path Planning Using Boustrophedon Cellular Decomposition Algorithm
FleverX/CppMaster
C++ Master Learning Roadmap, especially for AIoT and C++ advanced SWE
FleverX/dig-into-apollo
Apollo notes (Apollo学习笔记) - Apollo learning notes for beginners.
FleverX/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
FleverX/EPSILON
FleverX/grid_map
Universal grid map library for mobile robotic mapping
FleverX/grips
Gradient-Informed Path Smoothing for Wheeled Mobile Robots (GRIPS)
FleverX/hybrid-a-star-annotation
Hybrid A*路径规划器的代码注释
FleverX/hybrid-astar-planner
Hybrid A* Path Planner
FleverX/KDTree
Simple C++ KD-Tree implementation
FleverX/LeastSquareMethod
FleverX/mav_trajectory_generation
Polynomial trajectory generation and optimization, especially for rotary-wing MAVs.
FleverX/mpl_ros
A ROS wrapper for trajectory planning based on motion primitives
FleverX/octomap_ros
ROS package to provide conversion functions between ROS / PCL and OctoMap's native types.
FleverX/Papers
FleverX/path_planner
Hybrid A* Path Planner for the KTH Research Concept Vehicle
FleverX/path_smoother
smooth path/curve with Gradient Descent method
FleverX/polygon_coverage_planning
Coverage planning in general polygons with holes.
FleverX/PythonRobotics
Python sample codes for robotics algorithms.
FleverX/reinforcement-learning-code
FleverX/rpg_information_field
Information Field for Perception-aware Planning
FleverX/smartcar
自动驾驶系统实现
FleverX/teb_local_planner
An optimal trajectory planner considering distinctive topologies for mobile robots based on Timed-Elastic-Bands (ROS Package)