Global Path Planning and Path-Following for Wheeled Mobile Robot Using a Novel Control Structure Based on a Vision Sensor

被引:27
作者
Dirik, Mahmut [1 ]
Kocamaz, Adnan Fatih [1 ]
Castillo, Oscar [2 ]
机构
[1] Inonu Univ, Dept Comp Engn, TR-44280 Malatya, Turkey
[2] Tijuana Inst Technol, Tijuana 22414, Mexico
关键词
Path planning; Visual servoing; Soft computing; Image processing; Collision-free; PROBABILITY; NAVIGATION; ALGORITHM;
D O I
10.1007/s40815-020-00888-9
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper presents a novel design for the kinematic control structure of the wheeled mobile robot (WMR) path planning and path-following. The proposed system is focused on the implementation of practical real-time model-free algorithms based on visual servoing. The mainframe of this study is to implement a novel kinematic control structure based on visual sevoing and hybrid algorithms in real-time mobile robot applications. First, the structure of the proposed algorithm based on the visual information extracted from an overhead camera has been addressed. Then, the classification process of robot position and orientation, target, and obstacles has been addressed. Second, the path planning algorithms' initial parameters and obstacles-free path coordinates have been determined by visual information extracted from images in real time. In this step, the interval type-2 fuzzy inference (IT2FIS) algorithm and various algorithms used in path planning have been compared and their performances have been analyzed. The third stage handled the path-following process using a novel control structure for keeping up the robot on the generated path. In this step, the proposed approach is compared with fuzzy Type-1/Type-2 and fuzzy-PID control algorithms, and their results have been analyzed statistically. The proposed system has been successfully implemented on several maps. The experimental results show that the developed design is valid in generating collision-free paths efficiently and consistently and able to guide the robot to follow the path in real time.
引用
收藏
页码:1880 / 1891
页数:12
相关论文
共 39 条
[1]   Navigation of Mobile Robot Using Type-2 Fuzzy System [J].
Abiyev, Rahib H. ;
Erin, Besime ;
Denker, Ali .
INTELLIGENT COMPUTING METHODOLOGIES, ICIC 2017, PT III, 2017, 10363 :15-26
[2]   Sensor Fusion Based Model for Collision Free Mobile Robot Navigation [J].
Almasri, Marwah ;
Elleithy, Khaled ;
Alajlan, Abrar .
SENSORS, 2016, 16 (01)
[3]  
[Anonymous], J PHYS A
[4]  
Aye YY, 2017, DESIGN IMAGE BASED F
[5]  
Baklouti N., 2012, Journal of Intelligent Learning Systems and Applications, V4, P291
[6]   FUZZY REASONING AS A BASE FOR COLLISION AVOIDANCE DECISION SUPPORT SYSTEM [J].
Brcko, Tanja ;
Svetak, Jelenko .
PROMET-TRAFFIC & TRANSPORTATION, 2013, 25 (06) :555-564
[7]  
Bruce J, 2002, 2002 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS, VOLS 1-3, PROCEEDINGS, P2383, DOI 10.1109/IRDS.2002.1041624
[8]  
Castillo O, 2013, STUDIES FUZZINESS SO, V298, P91, DOI [10.1007/978-3-642-35641-4_14, DOI 10.1007/978-3-642-35641-4_14]
[9]  
Castillo O, 2007, GRC: 2007 IEEE INTERNATIONAL CONFERENCE ON GRANULAR COMPUTING, PROCEEDINGS, P145
[10]  
Castillo O, 2012, STUD FUZZ SOFT COMP, V272, P3, DOI 10.1007/978-3-642-24663-0