Research On The Path Planning Technology Of 3D Space Mobile Robot

In the area of intelligent robot,path planning is not only an important part for achieving robot autonomous navigation but also the scholars' research emphasis.In order to improve the 3D space mobile robot's autonomous navigation ability,we start an in-depth study on the path planning technology of wheeled mobile robot and quadcopter,which is based on sufficient survey of the present situation and development trend of space mobile robot's path planning technology.The main research contents include the following aspects:Firstly,we build the kinematic model of wheeled mobile robot and dynamic model of quadcopter,then we construct the wheeled mobile robot's pose transformation model and quadcopter's arrival point movement model based on the kinematic model,the dynamic model and the requirement of path planning mission.Secondly,we use A* algorithm to construct space mobile robot's global path planning model by considering the requirement of 3D space mobile robot.First of all,we use B-spline technology and A* algorithm to construct wheeled mobile robot's global path planning model considering its kinematic constraints in 2D grid environment,then considering quadcopter's dynamic properties,we expand A* algorithm from 2D environment to 3D environment and construct quadcopter's global path planning model based on the improved A* algorithm.Thirdly,considering the requirement of 3D space mobile robot's path planning in dynamic environment which the motion of dynamic obstacles is known,a dynamic RRT-Goalbiasing algorithm is proposed.First of all,we improve this algorithm's node expansion according to wheeled mobile robot's kinematic constraints and construct the wheeled mobile robot's dynamic path planning model,then we expand the dynamic RRT-Goalbiasing algorithm to 3D environment according to quadcopter's dynamic properties and construct the quadcopter's dynamic path planning model.At last,we construct a simulation platform by MATLAB GUI IDE which includes environment building model,planning method and algorithm choosing model,algorithm parameters setting model and result display model and test the proposed algorithms' effectiveness by this platform and proposed control model.