Multi Robot Path Planning Parameter Analysis Based on Particle Swarm Optimization (PSO) in an Intricate Unknown Environments
Shubham Shukla, NK Shukla, Vibhav Kumar Sachan
- 发表年份
- 2019
- 引用次数
- 8
摘要
Through Particle Swarm Optimization (PSO) path planning in an intricate environment turns out to be a novel approach for robot's multi path planning. Automation and detection capabilities of robots are the major challenges, to overcome these problems optimized path needs to be established. Robot path planning is one of the main problem that deals with the computation of collision free path for the given robot (agent) with the map, which helps it to operate. When the environment is known and the target location is estimated then only the path establishment is possible. The work we have presented on our paper totally focusses on the path planning problem. We have taken only one case into consideration, according to it the robot (agent) tracks the coordinated targets and reach towards the unknown environment through obstacle avoidance technique when the location of the target is unknown. Important parameters that we have taken to asses these algorithms are: (a) Number of visited node we consider as (Move). (b) Area explored considered as (Coverage). (c) Distance travelled considered as (Energy) and time elapsed as (Time).
关键词
相关论文
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Artificial intelligence: a modern approach
1995
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991
A new optimizer using particle swarm theory
R.C. Eberhart, James Kennedy
2002