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 >

Muhatasim Intisar¹, Mohammad Monirujjaman Khan^1,*, Mehedi Masud², Mohammad Shorfuzzaman²

Intelligent Automation & Soft Computing, Vol.31, No.1, pp. 101-115, 2022, DOI:10.32604/iasc.2022.019083

Abstract Paralysis is detrimental to people in catastrophic ways: losing income opportunities, becoming a burden to their friends and family, further physical deterioration, and the combination of these occurrences can often lead to depression. In third world countries, suffering from paralysis can be extra deleterious, where a large proportion of the population is engaged in some form of physical labor. The number of people exposed to paralysis risk factors is also increasing, with more and more people having hypertension, smoking, and other abnormalities. Besides, low workplace safety precautions may lead to an increased risk of spinal cord injury in developing nations.… 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 >

Jie Kang^1,*, Xiaoying Chen¹, Hu Cong², Chenghan Yang¹

Journal of New Media, Vol.3, No.3, pp. 81-87, 2021, DOI:10.32604/jnm.2021.017368

Abstract As a new product of the development of modern science and technology, the research and development of logistics robot has become the focus of social attention. Robot sorting and handling is the designated project of Jiangsu University Robot Competition. According to the requirements of the competition, this paper designs a kind of logistics robot trolley which can identify and grab materials according to a given path and transport them to a predetermined location. The mechanical structure design, driving motor selection and mechanical checking calculation of the car are mainly completed. According to the later experiments, the results show that the… More >

Ting-Hsuan Chien^1,*, Cheng-Yan Siao², Rong-Guey Chang²

Intelligent Automation & Soft Computing, Vol.29, No.3, pp. 827-838, 2021, DOI:10.32604/iasc.2021.018256

Abstract This paper describes a real-time simulator that allows the user in the factories to simulate arbitrary interaction between machinery and equipment. We discussed in details not only the general technique for developing such a real-time simulator but also the implementation of the simulator in its actual use. As such, people on the production line could benefit from observing and controlling robots in factories for preventing or reducing the severity of a collision, using the proposed simulator and its related technique. For that purpose, we divided the simulator into two main models: the real-time communication model and the simulation model. For… More >

Jhe-Wei Lin¹, Cheng-Yan Siao¹, Ting-Hsuan Chien^2,*, Rong-Guey Chang¹

Intelligent Automation & Soft Computing, Vol.29, No.3, pp. 685-695, 2021, DOI:10.32604/iasc.2021.018254

Abstract Since the rapid growth of the Fourth Industrial Revolution (or Industry 4.0), robots have been widely used in many applications. In the catering industry, robots are used to replace people to do routine jobs. Because meal is an important part of the catering industry, we aim to design and develop a robot to deliver meals for saving cost and improving a restaurant’s performance in this paper. However, for the existing meal delivery system, the guests must make their meals by themselves. To let the food delivery system become more user-friendly, we integrate an automatic guided vehicle (AGV) and a robotic… 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 >

Heonmoo Kim, Yosoon Choi^*

CMES-Computer Modeling in Engineering & Sciences, Vol.127, No.3, pp. 943-964, 2021, DOI:10.32604/cmes.2021.015300

Abstract In underground mine environments where various hazards exist, such as tunnel collapse, toxic gases, the application of autonomous robots can improve the stability of exploration and efficiently perform repetitive exploratory operations. In this study, we developed a small autonomous driving robot for unmanned environmental monitoring in underground mines. The developed autonomous driving robot controls the steering according to the distance to the tunnel wall measured using the light detection and ranging sensor mounted on the robot to estimate its location by simultaneously considering the measured values of the inertial measurement unit and encoder sensors. In addition, the robot autonomously drives… More >

Rihem Farkh^1,2, Haykel Marouani^1,*, Khaled Al Jaloud¹, Saad Alhuwaimel³, Mohammad Tabrez Quasim⁴, Yasser Fouad¹

CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 2189-2203, 2021, DOI:10.32604/cmc.2021.015906

Abstract The COVID-19 pandemic has shown that there is a lack of healthcare facilities to cope with a pandemic. This has also underscored the immediate need to rapidly develop hospitals capable of dealing with infectious patients and to rapidly change in supply lines to manufacture the prescription goods (including medicines) that is needed to prevent infection and treatment for infected patients. The COVID-19 has shown the utility of intelligent autonomous robots that assist human efforts to combat a pandemic. The artificial intelligence based on neural networks and deep learning can help to fight COVID-19 in many ways, particularly in the control… More >

Mohammed Ibrahim Ahmed Al-mashhadani¹, Theyazn H. H. Aldhyani^2,*, Mosleh Hmoud Al-Adhaileh³, Alwi M. Bamhdi⁴, Mohammed Y. Alzahrani⁵, Fawaz Waselallah Alsaade⁶, Hasan Alkahtani^1,6

Computer Systems Science and Engineering, Vol.38, No.1, pp. 25-37, 2021, DOI:10.32604/csse.2021.014992

Abstract Touch gesture recognition is an important aspect in human–robot interaction, as it makes such interaction effective and realistic. The novelty of this study is the development of a system that recognizes human–animal affective robot touch (HAART) using a deep learning algorithm. The proposed system was used for touch gesture recognition based on a dataset provided by the Recognition of the Touch Gestures Challenge 2015. The dataset was tested with numerous subjects performing different HAART gestures; each touch was performed on a robotic animal covered by a pressure sensor skin. A convolutional neural network algorithm is proposed to implement the touch… More >