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An open autonomous driving platform
Complete Coverage Path Planning Using Boustrophedon Cellular Decomposition Algorithm
C++ Master Learning Roadmap, especially for AIoT and C++ advanced SWE
Apollo notes (Apollo学习笔记) - Apollo learning notes for beginners.
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
Universal grid map library for mobile robotic mapping
vehicle/robot planning based on grid search algorithm
Gradient-Informed Path Smoothing for Wheeled Mobile Robots (GRIPS)
Hybrid A*路径规划器的代码注释
Hybrid A* Path Planner
Simple C++ KD-Tree implementation
Polynomial trajectory generation and optimization, especially for rotary-wing MAVs.
A ROS wrapper for trajectory planning based on motion primitives
ROS package to provide conversion functions between ROS / PCL and OctoMap's native types.
Hybrid A* Path Planner for the KTH Research Concept Vehicle
smooth path/curve with Gradient Descent method
Coverage planning in general polygons with holes.
Python sample codes for robotics algorithms.
Information Field for Perception-aware Planning
自动驾驶系统实现
An optimal trajectory planner considering distinctive topologies for mobile robots based on Timed-Elastic-Bands (ROS Package)
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.