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Studies On Path Planning Of The Small Unmanned Ground Mobile Platform

Posted on:2015-11-25Degree:DoctorType:Dissertation
Country:ChinaCandidate:J LiuFull Text:PDF
GTID:1228330452964799Subject:Weapons systems, and application engineering
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This paper conducted in-depth research, mainly for the small unmanned groundmobile platforms (SUGMP) path planning techniques. The main research contentsControl system of small unmanned mobile platform, global path planning of the smallunmanned mobile platform based on the known map, local navigation and obstacleavoidance planning, and mobile platform positioning and integrated control etc.First, the paper analyses and designs the control system of small unmanned groundmobile platform for the overall, and determines the overall scheme of the controlarchitecture. This paper also designs the path planning scheme of the SUGMP, andoverall designs each function module; analyses the driving performance on the mobileplatform, and establishes the kinematics model of the mobile platform.Second, to the global path planning with a known environment map, we use thestrategies of the improved ant colony algorithm and geometric Combination to obtain theglobally optimal path planning. Firstly, through using the environment-raster mapconversion principle, combining obstacle performance mobile platform, theenvironmental map-raster map conversion rules are established; Secondly, based onanalyzing the principle of the ant colony algorithm, from the designs updating pheromoneof ant colony, the ant colony global path planning algorithm based on grid map wasdesigned; Thirdly, from the geometrical principle, path planning algorithms have beenoptimized to further shorten the planning time, a global path planning of mobileplatforms geometric colony optimization algorithm is established. And throughsimulation, the shortest planning path and time both proved the algorithm’s practicalityand reliability;the results of comprehensive performance index evaluation show that theant colony geometry optimization algorithm has good comprehensive performance.Moreover, to the local path planning problem, the paper designs three platformcontrol module: navigation, obstacle avoidance and collision avoidance–path tracking.Among them, the navigation module is mainly used for the platform control in a securityno-obstacle environment, mobile platform mainly relies on the navigation module tofinish the global path tracking; the obstacle avoidance module uses the rangefinder-2Dlaser radar sensor, through analysing the forward environmental data, establishes the freesectors in an adaptive threshold, then selects the optimal sector, and finally determinesthe direction of the platform;the collision avoidance–path tracking module with sonar sensor fixed on the mobile platform, ensured the front obstacle avoidance and walkingalong the wall. The simulation results show that the three kinds of control algorithm cancontrol the mobile platform perfectly to reach the target point.Again, using Kalman filtering method handled the GPS/ARHS sensor data for thefusion processing, getting the position and attitude information of the platform. Bystudying the problem of sensor information mutation, this paper puts forward a newtheory criterion, and uses the corresponding strong tracking Kalman filter to solve theproblem. Simulation results shows that, to the data field value problems caused by theerrors of the sensor, the strong tracking Kalman filter can be very good to solve themutation position information. On the path planning scheme, behavior arbiter controlleris designed to solve the control behavior’s priority.Last, experiments were conducted for three aspects of the path planning to theSUGMP: Navigation control, obstacle avoidance, navigation and obstacle avoidancecontrol integrated control; the experimental results show that, this scheme can wellcontrol the mobile platform with the optimal cost for independent travel the shortest path,finish the path planning task.
Keywords/Search Tags:Global path planning, ant colony algorithm, local path planning, navigation, obstacle avoidance and collision avoidance, positioning, control
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