Mobile robot safe navigation in unknown environment

Shayestegan, Mohsen; Marhaban, Mohammad Hamiruce

doi:10.1109/iccsce.2012.6487113

Cited by 9 publications

(3 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Several advanced control algorithms have been proposed to guarantee successful navigation in real-world applications. The authors [1], [6], [8], [11], [13] have designed various types of Intelligent controller based on fuzzy logic technique and optimized model of fuzzy logic controller for obstacle avoidance of mobile robot. They have verified that design of ordinal structure fuzzy logic is easier than conventional fuzzy logic controller.…”

Section: Related Workmentioning

confidence: 99%

Path Planning and Control of Autonomous Robotic Agent Using Mamdani Based Fuzzy Logic Controller and ARDUINO UNO Micro Controller

Panigrahi

Sahoo

2015

Advances in Intelligent Systems and Computing

View full text Add to dashboard Cite

Abstract. The autonomous mobile robots are used for various purposes like materials transportation, nuclear and military environments etc. In this paper fuzzy logic technique is used for controlling the mobile robot in an unknown environment. The main goal of robot is to reach the target point from a starting point with avoiding obstacles in the way. The Mamdani fuzzy logic controller is used to obtain collision free path where inputs are front obstacle distance (FOD), left obstacle distance (LOD), right obstacle distance (ROD), heading angle (HA) and the output corresponds to the steering angle (SA) of the mobile robot. The effectiveness of the controller is verified using Mamdani fuzzy inference system.

show abstract

Section: Related Workmentioning

confidence: 99%

Path Planning and Control of Autonomous Robotic Agent Using Mamdani Based Fuzzy Logic Controller and ARDUINO UNO Micro Controller

Panigrahi

Sahoo

2015

Advances in Intelligent Systems and Computing

View full text Add to dashboard Cite

show abstract

“…Along with these developments, applications and tasks that robots can perform are becoming increasingly complex and complicated, especially in mobile robots. In addition, mobile robots must also be equipped with good navigation algorithms to move into the target position without crashing into any objects around them while completing their tasks (Shayestegan & Marhaban, 2012). A mobile robot with a holonomic system like Omni directional mobile robot can move freely in all directions without changing its heading orientation (Afridi & Usman, 2019).…”

Section: Introductionmentioning

confidence: 99%

Development of an Omni Directional based Mobile Robot Navigation System using Optimized-Fuzzy Social Force Model

2022

View full text Add to dashboard Cite

Membangun sebuah sistem navigasi pada mobile robot yang bergerak di ruang sosial perlu memperhatikan beberapa aspek krusial, seperti menghindari rintangan, menjaga arah hadap robot ke tujuan, dan mencapai tujuan dengan cepat. Penelitian ini bertujuan untuk mengembangkan sistem navigasi pada Omnidirectional mobile robot menggunakan Fuzzy-Social Force Model (FSFM). Social Force Model (SFM) mampu menggerakan robot ke tujuan sambil menghindari rintangan. Fuzzy Inference System (FIS) digunakan untuk menghasilkan gain adaptif sebagai salah satu parameter SFM agar respon SFM sesuai dengan masukan dari sensor lidar. Aturan FIS dioptimasi agar mendapatkan nilai optimal menggunakan Particle Swarm Optimization (PSO). Dari hasil percobaan, mobile robot mencapai tujuan lebih cepat dengan selisih 1.59 s dan nilai error heading robot lebih kecil 0.9261 dibandingkan FSFM tanpa optimasi.

show abstract

“…The robot controller can be programmed using the built-in integrated development environment. The simulator has been used by the researchers for controlling the wheeled [16] as well as legged robots [17][18].…”

Section: Introductionmentioning

confidence: 99%

A 2D simulator for vision based autonomous road following

Farooq

Amar

Asad

2013

2013 IEEE International Conference on Robotics and Biomimetics (ROBIO)

View full text Add to dashboard Cite

A 2D simulator for vision based autonomous road following is designed using MATLAB. The simulator provides options for selecting road image, placing hurdles on road and the algorithm for following the road autonomously. With the road image containing hurdles and algorithm selected, the simulator draws the robot trajectory and also plots the error curves. A real time implementation of simulated algorithms is finally presented. The simulator can be employed to teach the fundamental concepts in autonomous road following tasks.

show abstract

Mobile robot safe navigation in unknown environment

Cited by 9 publications

References 15 publications

Path Planning and Control of Autonomous Robotic Agent Using Mamdani Based Fuzzy Logic Controller and ARDUINO UNO Micro Controller

Path Planning and Control of Autonomous Robotic Agent Using Mamdani Based Fuzzy Logic Controller and ARDUINO UNO Micro Controller

Development of an Omni Directional based Mobile Robot Navigation System using Optimized-Fuzzy Social Force Model

A 2D simulator for vision based autonomous road following

Contact Info

Product

Resources

About