scholarly journals UAV Path Planning System Based on 3D Informed RRT* for Dynamic Obstacle Avoidance

2018 ◽  
Author(s):  
Jiawei Meng ◽  
Vijay M. Pawar ◽  
Sebastian Kay ◽  
Angran Li
Keyword(s):  
Path Planning ◽  
Obstacle Avoidance ◽  
Planning System ◽  
Dynamic Obstacle Avoidance ◽  
Dynamic Obstacle

scholarly journals An Improved VFF Approach for Robot Path Planning in Unknown and Dynamic Environments

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Jianjun Ni ◽  
Wenbo Wu ◽  
Jinrong Shen ◽  
Xinnan Fan
Keyword(s):  
Path Planning ◽  
Obstacle Avoidance ◽  
Dynamic Environments ◽  
Minimum Problem ◽  
Robot Path Planning ◽  
Virtual Force ◽  
Dynamic Obstacle Avoidance ◽  
Dynamic Obstacle ◽  
Local Minimum Problem ◽  
Robot Path

Robot path planning in unknown and dynamic environments is one of the hot topics in the field of robot control. The virtual force field (VFF) is an efficient path planning method for robot. However, there are some shortcomings of the traditional VFF based methods, such as the local minimum problem and the higher computational complexity, in dealing with the dynamic obstacle avoidance. In this paper, an improved VFF approach is proposed for the real-time robot path planning, where the environment is unknown and changing. An area ratio parameter is introduced into the proposed VFF based approach, where the size of the robot and obstacles are considered. Furthermore, a fuzzy control module is added, to deal with the problem of obstacle avoidance in dynamic environments, by adjusting the rotation angle of the robot. Finally, some simulation experiments are carried out to validate and demonstrate the efficiency of the proposed approach.

Online Heuristically Planning for Relative Optimal Paths Using a Stochastic Algorithm for USVs

2019 ◽  
Vol 73 (2) ◽  
pp. 485-508
Author(s):  
Naifeng Wen ◽  
Rubo Zhang ◽  
Guanqun Liu ◽  
Junwei Wu
Keyword(s):  
Path Planning ◽  
Obstacle Avoidance ◽  
Optimal Path ◽  
Stochastic Algorithm ◽  
Proportional Navigation ◽  
Reference Information ◽  
International Regulations ◽  
Dynamic Obstacle Avoidance ◽  
Dynamic Obstacle ◽  
Local Path

This paper attempts to solve a challenge in online relative optimal path planning of unmanned surface vehicles (USVs) caused by current and wave disturbance in the practical marine environment. The asymptotically optimal rapidly extending random tree (RRT*) method for local path optimisation is improved. Based on that, an online path planning (OPP) scheme is proposed according to the USV's kinematic and dynamic model. The execution efficiency of RRT* is improved by reduction of the sampling space that is used for randomly learning environmental knowledge. A heuristic sampling scheme is proposed based on the proportional navigation guidance (PNG) method that is used to enable the OPP procedure to utilise the reference information of the global path. Meanwhile, PNG is used to guide RRT* in generating feasible paths with a small amount of gentle turns. The dynamic obstacle avoidance problem is also investigated based on the International Regulations for Preventing Collisions at Sea. Case studies demonstrate that the proposed method efficiently plans paths that are relatively easier to execute and lower in fuel expenditure than traditional schemes. The dynamic obstacle avoidance ability of the proposed scheme is also attested.

Dynamic obstacle avoidance path planning

2014 ◽  
Author(s):  
Shun-Feng Su ◽  
Ming-Chang Chen ◽  
Chung-Ying Li ◽  
Wei-Yen Wang ◽  
Wen-June Wang
Keyword(s):  
Path Planning ◽  
Obstacle Avoidance ◽  
Dynamic Obstacle Avoidance ◽  
Dynamic Obstacle
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