A new path planner for autonomous mobile robots based on genetic algorithm

2010 ◽  
Author(s):  
Pirooz Shamsinejad ◽  
Mohammad Saraee ◽  
Farid Sheikholeslam
Keyword(s):  
Genetic Algorithm ◽  
Mobile Robots ◽  
Autonomous Mobile Robots ◽  
Path Planner

scholarly journals Chaotic Path Planner of Autonomous Mobile Robots Based on the Standard Map for Surveillance Missions

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Caihong Li ◽  
Yong Song ◽  
Fengying Wang ◽  
Zhenying Liang ◽  
Baoyan Zhu
Keyword(s):  
Mobile Robot ◽  
Mobile Robots ◽  
Small Region ◽  
Autonomous Mobile Robots ◽  
Large Region ◽  
Standard Map ◽  
Path Planner

This paper proposes a fusion iterations strategy based on the Standard map to generate a chaotic path planner of the mobile robot for surveillance missions. The distances of the chaotic trajectories between the adjacent iteration points which are produced by the Standard map are too large for the robot to track. So a fusion iterations strategy combined with the large region iterations and the small grids region iterations is designed to resolve the problem. The small region iterations perform the iterations of the Standard map in the divided small grids, respectively. It can reduce the adjacent distances by dividing the whole surveillance workspace into small grids. The large region iterations combine all the small grids region iterations into a whole, switch automatically among the small grids, and maintain the chaotic characteristics of the robot to guarantee the surveillance missions. Compared to simply using the Standard map in the whole workspace, the proposed strategy can decrease the adjacent distances according to the divided size of the small grids and is convenient for the robot to track.

scholarly journals An Improved Chaotic Motion Path Planner for Autonomous Mobile Robots Based on a Logistic Map

10.5772/56587 ◽  
2013 ◽  
Vol 10 (6) ◽  
pp. 273 ◽  
Author(s):  
Caihong Li ◽  
Fengying Wang ◽  
Lei Zhao ◽  
Yibin Li ◽  
Yong Song
Keyword(s):  
Mobile Robots ◽  
Chaotic Motion ◽  
Logistic Map ◽  
Autonomous Mobile Robots ◽  
Motion Path ◽  
Path Planner

scholarly journals An Optimal Footprint Based Coverage Planning for Hydro Blasting Robots

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1194
Author(s):  
Thejus Pathmakumar ◽  
Madan Mohan Rayguru ◽  
Sriharsha Ghanta ◽  
Manivannan Kalimuthu ◽  
Mohan Rajesh Elara
Keyword(s):  
Genetic Algorithm ◽  
Mobile Robots ◽  
Numerical Simulations ◽  
Labour Force ◽  
Successful Implementation ◽  
Multi Objective Optimization ◽  
Metallic Surfaces ◽  
Industrial Sites ◽  
Experimental Trials ◽  
Time And Energy

The hydro blasting of metallic surfaces is an essential maintenance task in various industrial sites. Its requirement of a considerable labour force and time, calls for automating the hydro blasting jobs through mobile robots. A hydro blasting robot should be able to cover the required area for a successful implementation. If a conventional robot footprint is chosen, the blasting may become inefficient, even though the concerned area is completely covered. In this work, the blasting arm’s sweeping angle is chosen as the robot’s footprint for hydro blasting task, and a multi-objective optimization-based framework is proposed to compute the optimal sweeping arc. The genetic algorithm (GA) methodology is exploited to compute the optimal footprint, which minimizes the blasting time and energy simultaneously. Multiple numerical simulations are performed to show the effectiveness of the proposed approach. Moreover, the strategy is successfully implemented on our hydro blasting robot named Hornbill, and the efficacy of the proposed approach is validated through experimental trials.

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