Optimal path planning and execution for mobile robots using genetic algorithm and adaptive fuzzy-logic control

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• 作者：Azzeddine Bakdi^a ; ^b ; ^{bkdaznsun@gmail.com}Author Vitae ; Abdelfetah Hentout^a ; ^{ahentout@cdta.dz}Author Vitae ; Hakim Boutami^a ; ^b ; ^{Hakim08boutami@gmail.com}Author Vitae ; Abderraouf Maoudj^a ; ^{amaoudj@cdta.dz}Author Vitae ; Ouarda Hachour^b ; ^{hachour_ouarda@yahoo.fr}Author Vitae ; Brahim Bouzouia^a ; ^{bbouzouia@cdta.dz}Author Vitae
• 关键词：Mobile robot ; Off-line optimal path planning ; Path execution ; Genetic algorithm ; Adaptive fuzzy-logic control ; Two-Kinect cameras system
• 刊名：Robotics and Autonomous Systems
• 出版年：2017
• 出版时间：March 2017
• 年：2017
• 卷：89
• 期：Complete
• 页码：95-109
• 全文大小：4817 K
• 卷排序：89

文摘

Exact representation of the mobile robot and the obstacles dimensions, location and shapes. Objective function leads to optimal solutions in terms of (i) minimum path length, (ii) maximum safety, and (iii) shortest trajectory execution time. PCHIP path smoothing reduces accelerations and increases the average velocity of the robot for faster trajectory execution in a high-resolution map representation. AFL controller allows the robot to track and minimize the errors during trajectory execution. GA-PCHIP approach with Kinect cameras allow indoor mobile robots to safely navigate inside highly constrained environments. Ensures optimal maneuvering in a limited workspace with obstacles. Faster than the conventional methods found in the literature.