OBCA-master

所属分类:matlab编程
开发工具:matlab
文件大小:9990KB
下载次数:11
上传日期:2019-05-22 09:23:21
上 传 者52丫丫
说明:  可以实现车辆避碰和路径规划,文档中有效果动图。可参考
(Vehicle collision avoidance and path planning can be realized, and effective motion maps can be found in the documents. May refer to)

文件列表:
AutonomousParking (0, 2018-04-27)
AutonomousParking\DualMultWS.jl (3414, 2018-04-27)
AutonomousParking\ParkingConstraints.jl (5378, 2018-04-27)
AutonomousParking\ParkingDist.jl (10584, 2018-04-27)
AutonomousParking\ParkingSignedDist.jl (10628, 2018-04-27)
AutonomousParking\a_star.jl (10071, 2018-04-27)
AutonomousParking\collision_check.jl (3654, 2018-04-27)
AutonomousParking\hybrid_a_star.jl (18336, 2018-04-27)
AutonomousParking\main.jl (8986, 2018-04-27)
AutonomousParking\obstHrep.jl (3021, 2018-04-27)
AutonomousParking\plotTraj.jl (4057, 2018-04-27)
AutonomousParking\reeds_shepp.jl (25260, 2018-04-27)
AutonomousParking\setup.jl (2102, 2018-04-27)
AutonomousParking\veloSmooth.jl (3220, 2018-04-27)
LICENSE (35147, 2018-04-27)
QuadcopterNavigation (0, 2018-04-27)
QuadcopterNavigation\QuadcopterDist.jl (10048, 2018-04-27)
QuadcopterNavigation\QuadcopterSignedDist.jl (10584, 2018-04-27)
QuadcopterNavigation\a_star_3D.jl (12775, 2018-04-27)
QuadcopterNavigation\constrSatisfaction.jl (7578, 2018-04-27)
QuadcopterNavigation\mainQuadcopter.jl (4935, 2018-04-27)
QuadcopterNavigation\plotTrajQuadcopter.jl (7169, 2018-04-27)
QuadcopterNavigation\setupQuadcopter.jl (1453, 2018-04-27)
images (0, 2018-04-27)
images\TrajBack_ParkingVideo.gif (998710, 2018-04-27)
images\TrajPar_ParkingVideo.gif (987704, 2018-04-27)
images\TrajQuad_3D_Video.gif (7380830, 2018-04-27)
images\TrajTrailer_ParkingVideo.gif (1185580, 2018-04-27)

# OBCA Optimization-Based Collision Avoidance - a path planner for autonomous navigation Paper describing the theory can be found [here](http://arxiv.org/abs/1711.03449). *Note*: An OBCA version specialized towards autonomous parking can be found at [H-OBCA](https://github.com/XiaojingGeorgeZhang/H-OBCA). ## Short Description OBCA is a novel method for formulating collision avoidance constraints. It provides a smooth reformulation of collision avoidance constraints, allowing the use of generic non-linear optimization solvers. OBCA can be used to in path planning algorithms to generate *high-quality paths* that satisfy the system dynamics as well as satefy constraints. We provide [Julia](https://julialang.org/)-based implementations for a quadcopter navigation problem and for autonomous parking problems. ## Examples ### OBCA for Quadcopter Navigation ### OBCA for Autonomous Parking #### Backwards Parking #### Parallel Parking #### Parking of Truck with Trailer

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