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  • Open Access


    Mobile Robots’ Collision Prediction Based on Virtual Cocoons

    Virginijus Baranauskas1,*, 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 >

  • Open Access


    Tour Planning Design for Mobile Robots Using Pruned Adaptive Resonance Theory Networks

    S. Palani Murugan1,*, 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 >

  • Open Access


    Energy Saving Control Approach for Trajectory Tracking of Autonomous Mobile Robots

    Yung-Hsiang Chen1, Yung-Yue Chen2, Shi-Jer Lou3, Chiou-Jye Huang4,*

    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 >

  • Open Access


    A Deep Learning Approach for the Mobile-Robot Motion Control System

    Rihem Farkh1,4,*, 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 >

  • Open Access


    Mobile Robots Navigation Modeling in Known 2D Environment Based on Petri Nets

    S. Bartkeviciusa, O. Fiodorovab, A. Knysc, A. Derviniened, G. Dervinisc, V. Raudonisc, A. Lipnickasc, V. Baranauskasc, K. Sarkauskasc, L. Balaseviciusc

    Intelligent Automation & Soft Computing, Vol.24, No.2, pp. 241-248, 2018, DOI:10.1080/10798587.2016.1264695

    Abstract The paper deals with supervised robot navigation in known environments. The navigation task is divided into two parts, where one part of the navigation is done by the supervisor system i.e. the system sets the vector marks on the salient edges of the virtual environment map and guides the robot to reach these marks. Mobile robots have to perform a specific task according to the given paths and solve the local obstacles avoidance individually. The salient point’s detection, vector mark estimation and optimal path calculation are done on the supervisor computer using colored Petri nets. The proposed approach was extended… More >

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