Zhen Xu¹, Shuai Guo^1,2,*, Tao Song¹, Yuwen Li¹, Lingdong Zeng¹

CMES-Computer Modeling in Engineering & Sciences, Vol.130, No.3, pp. 1853-1882, 2022, DOI:10.32604/cmes.2022.018004

Abstract The effectiveness of mobile robot aided for architectural construction depends strongly on its accurate localization ability. Localization of mobile robot is increasingly important for the printing of buildings in the construction scene. Although many available studies on the localization have been conducted, only a few studies have addressed the more challenging problem of localization for mobile robot in large-scale ongoing and featureless scenes. To realize the accurate localization of mobile robot in designated stations, we build an artificial landmark map and propose a novel nonlinear optimization algorithm based on graphs to reduce the uncertainty of the whole map. Then, the… More >

Virginijus Baranauskas^1,*, Žydrūnas Jakas¹, Kastytis Kiprijonas Šarkauskas¹, Stanislovas Bartkevičius², Gintaras Dervinis¹, Alma Dervinienė³, Leonas Balaševičius¹, Vidas Raudonis¹, Renaldas Urniežius¹, Jolanta Repšytė¹

Intelligent Automation & Soft Computing, Vol.32, No.3, pp. 1343-1356, 2022, DOI:10.32604/iasc.2022.022288

Abstract The research work presents a collision prediction method of mobile robots. The authors of the work use so-called, virtual cocoons to evaluate the collision criteria of two robots. The idea, mathematical representation of the calculations and experimental simulations are presented in the paper work. A virtual model of the industrial process with moving mobile robots was created. Obstacle avoidance was not solved here. The authors of the article were working on collision avoidance problem solving between moving robots. Theoretical approach presents mathematical calculations and dependences of path angles of mobile robots. Experimental simulations, using the software Centaurus CPN, based on… More >

Aisha Muhammad^1,5, Mohammed A. H. Ali^2,*, Sherzod Turaev³, Ibrahim Haruna Shanono^4,5, Fadhl Hujainah⁶, Mohd Nashrul Mohd Zubir², Muhammad Khairi Faiz², Erma Rahayu Mohd Faizal¹, Rawad Abdulghafor⁸

CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2697-2719, 2022, DOI:10.32604/cmc.2022.020873

Abstract This paper presents a development of a novel path planning algorithm, called Generalized Laser simulator (GLS), for solving the mobile robot path planning problem in a two-dimensional map with the presence of constraints. This approach gives the possibility to find the path for a wheel mobile robot considering some constraints during the robot movement in both known and unknown environments. The feasible path is determined between the start and goal positions by generating wave of points in all direction towards the goal point with adhering to constraints. In simulation, the proposed method has been tested in several working environments with… More >

Wei-Cheng Wang, Chow-Yong Ng, Rongshun Chen^*

Intelligent Automation & Soft Computing, Vol.32, No.2, pp. 991-1006, 2022, DOI:10.32604/iasc.2022.022067

Abstract Path planning is intrinsically regarded as a multi-objective optimization problem (MOOP) that simultaneously optimizes the shortest path and the least collision-free distance to obstacles. This work develops a novel optimized approach using the genetic algorithm (GA) to drive the multi-objective evolutionary algorithm (MOEA) for the path planning of a mobile robot in a given finite environment. To represent the positions of a mobile robot as integer-type genes in a chromosome of the GA, a grid-based method is also introduced to relax the complex environment to a simple grid-based map. The system architecture is composed of a mobile robot, embedded with… More >

S. Palani Murugan^1,*, M. Chinnadurai¹, S. Manikandan²

CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 181-194, 2022, DOI:10.32604/cmc.2022.016152

Abstract The development of intelligent algorithms for controlling autonom- ous mobile robots in real-time activities has increased dramatically in recent years. However, conventional intelligent algorithms currently fail to accurately predict unexpected obstacles involved in tour paths and thereby suffer from inefficient tour trajectories. The present study addresses these issues by proposing a potential field integrated pruned adaptive resonance theory (PPART) neural network for effectively managing the touring process of autonomous mobile robots in real-time. The proposed system is implemented using the AlphaBot platform, and the performance of the system is evaluated according to the obstacle prediction accuracy, path detection accuracy, time-lapse,… More >

Yung-Hsiang Chen¹, Yung-Yue Chen², Shi-Jer Lou³, Chiou-Jye Huang^4,*

Intelligent Automation & Soft Computing, Vol.31, No.1, pp. 357-372, 2022, DOI:10.32604/iasc.2022.018663

Abstract This research presents an adaptive energy-saving H₂ closed-form control approach to solve the nonlinear trajectory tracking problem of autonomous mobile robots (AMRs). The main contributions of this proposed design are as follows: closed-form approach, simple structure of the control law, easy implementation, and energy savings through trajectory tracking design of the controlled AMRs. It is difficult to mathematically obtained this adaptive H₂ closed-form solution of AMRs. Therefore, through a series of mathematical analyses of the trajectory tracking error dynamics of the controlled AMRs, the trajectory tracking problem of AMRs can be transformed directly into a solvable problem, and an adaptive… More >

Rihem Farkh^1,4,*, Khaled Al jaloud¹, Saad Alhuwaimel², Mohammad Tabrez Quasim³, Moufida Ksouri⁴

Intelligent Automation & Soft Computing, Vol.29, No.2, pp. 423-435, 2021, DOI:10.32604/iasc.2021.016219

Abstract A line follower robot is an autonomous intelligent system that can detect and follow a line drawn on floor. Line follower robots need to adapt accurately, quickly, efficiently, and inexpensively to changing operating conditions. This study proposes a deep learning controller for line follower mobile robots using complex decision-making strategies. An Arduino embedded platform is used to implement the controller. A multilayered feedforward network with a backpropagation training algorithm is employed. The network is trained offline using Keras and implemented on a ATmega32 microcontroller. The experimental results show that it has a good control effect and can extend its application. More >

Rihem Farkh^1,5,*, Mohammad Tabrez Quasim², Khaled Al jaloud¹, Saad Alhuwaimel³, Shams Tabrez Siddiqui⁴

CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 1065-1079, 2021, DOI:10.32604/cmc.2021.016600

Abstract With the development of artificial intelligence technology, various sectors of industry have developed. Among them, the autonomous vehicle industry has developed considerably, and research on self-driving control systems using artificial intelligence has been extensively conducted. Studies on the use of image-based deep learning to monitor autonomous driving systems have recently been performed. In this paper, we propose an advanced control for a serving robot. A serving robot acts as an autonomous line-follower vehicle that can detect and follow the line drawn on the floor and move in specified directions. The robot should be able to follow the trajectory with speed… More >

G. Mousa¹, Amr Almaddah², Ayman A. Aly^3,*

CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 2005-2023, 2021, DOI:10.32604/cmc.2020.012580

Abstract About 10–20% of every country’s population is disable. There are at least 650 million people with a kind of disability worldwide. Assistance and support are perquisites for many handicap people for participating in society. Electric powered wheelchairs provide efficient mobility to motor impaired persons. In this paper a smart controller of a wheel chair mobile robot using Particle Swarm Optimization Proportional controller (PSO-P) was proposed where (PSO) algorithm was utilized to tune the proportional controller’s gains for each axis. Aiming to improve wheelchair tracking trajectory, a kinematic model of a robot with linear and angular velocities parameters was developed. The… More >

MengYuan Chen^1,2

Intelligent Automation & Soft Computing, Vol.24, No.3, pp. 593-602, 2018, DOI:10.31209/2018.100000026

Abstract With the increasing number of feature points of a map, the dimension of systematic observation is added gradually, which leads to the deviation of the volume points from the desired trajectory and significant errors on the state estimation. An Iterative Squared-Root Cubature Kalman Filter (ISR-CKF) algorithm proposed is aimed at improving the SR-CKF algorithm on the simultaneous localization and mapping (SLAM). By introducing the method of iterative updating, the sample points are re-determined by the estimated value and the square root factor, which keeps the distortion small in the highly nonlinear environment and improves the precision further. A robust tracking… More >