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  • Open Access

    ARTICLE

    AI Safety Approach for Minimizing Collisions in Autonomous Navigation

    Abdulghani M. Abdulghani, Mokhles M. Abdulghani, Wilbur L. Walters, Khalid H. Abed*

    Journal on Artificial Intelligence, Vol.5, pp. 1-14, 2023, DOI:10.32604/jai.2023.039786

    Abstract Autonomous agents can explore the environment around them when equipped with advanced hardware and software systems that help intelligent agents minimize collisions. These systems are developed under the term Artificial Intelligence (AI) safety. AI safety is essential to provide reliable service to consumers in various fields such as military, education, healthcare, and automotive. This paper presents the design of an AI safety algorithm for safe autonomous navigation using Reinforcement Learning (RL). Machine Learning Agents Toolkit (ML-Agents) was used to train the agent with a proximal policy optimizer algorithm with an intrinsic curiosity module (PPO + ICM). This training… More >

  • Open Access

    ARTICLE

    Improved RRT Algorithm for Automatic Charging Robot Obstacle Avoidance Path Planning in Complex Environments

    Chong Xu1, Hao Zhu1, Haotian Zhu2, Jirong Wang1, Qinghai Zhao1,3,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.3, pp. 2567-2591, 2023, DOI:10.32604/cmes.2023.029152

    Abstract A new and improved RRT algorithm has been developed to address the low efficiency of obstacle avoidance planning and long path distances in the electric vehicle automatic charging robot arm. This algorithm enables the robot to avoid obstacles, find the optimal path, and complete automatic charging docking. It maintains the global completeness and path optimality of the RRT algorithm while also improving the iteration speed and quality of generated paths in both 2D and 3D path planning. After finding the optimal path, the B-sample curve is used to optimize the rough path to create a smoother More > Graphic Abstract

    Improved RRT<sup>∗</sup> Algorithm for Automatic Charging Robot Obstacle Avoidance Path Planning in Complex Environments

  • Open Access

    ARTICLE

    An Improved High Precision 3D Semantic Mapping of Indoor Scenes from RGB-D Images

    Jing Xin1,*, Kenan Du1, Jiale Feng1, Mao Shan2

    CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.3, pp. 2621-2640, 2023, DOI:10.32604/cmes.2023.027467

    Abstract This paper proposes an improved high-precision 3D semantic mapping method for indoor scenes using RGB-D images. The current semantic mapping algorithms suffer from low semantic annotation accuracy and insufficient real-time performance. To address these issues, we first adopt the Elastic Fusion algorithm to select key frames from indoor environment image sequences captured by the Kinect sensor and construct the indoor environment space model. Then, an indoor RGB-D image semantic segmentation network is proposed, which uses multi-scale feature fusion to quickly and accurately obtain object labeling information at the pixel level of the spatial point cloud More >

  • Open Access

    ARTICLE

    Systematic Survey on Big Data Analytics and Artificial Intelligence for COVID-19 Containment

    Saeed M. Alshahrani1, Jameel Almalki2, Waleed Alshehri2, Rashid Mehmood3, Marwan Albahar2, Najlaa Jannah2, Nayyar Ahmed Khan1,*

    Computer Systems Science and Engineering, Vol.47, No.2, pp. 1793-1817, 2023, DOI:10.32604/csse.2023.039648

    Abstract Artificial Intelligence (AI) has gained popularity for the containment of COVID-19 pandemic applications. Several AI techniques provide efficient mechanisms for handling pandemic situations. AI methods, protocols, data sets, and various validation mechanisms empower the users towards proper decision-making and procedures to handle the situation. Despite so many tools, there still exist conditions in which AI must go a long way. To increase the adaptability and potential of these techniques, a combination of AI and Bigdata is currently gaining popularity. This paper surveys and analyzes the methods within the various computational paradigms used by different researchers More >

  • Open Access

    ARTICLE

    Multitarget Flexible Grasping Detection Method for Robots in Unstructured Environments

    Qingsong Fan, Qijie Rao, Haisong Huang*

    CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.2, pp. 1825-1848, 2023, DOI:10.32604/cmes.2023.028369

    Abstract In present-day industrial settings, where robot arms perform tasks in an unstructured environment, there may exist numerous objects of various shapes scattered in random positions, making it challenging for a robot arm to precisely attain the ideal pose to grasp the object. To solve this problem, a multistage robotic arm flexible grasp detection method based on deep learning is proposed. This method first improves the Faster RCNN target detection model, which significantly improves the detection ability of the model for multiscale grasped objects in unstructured scenes. Then, a Squeeze-and-Excitation module is introduced to design a… More >

  • Open Access

    ARTICLE

    Computing and Implementation of a Controlled Telepresence Robot

    Ali A. Altalbe1,2,*, Aamir Shahzad3, Muhammad Nasir Khan4

    Intelligent Automation & Soft Computing, Vol.37, No.2, pp. 1569-1585, 2023, DOI:10.32604/iasc.2023.039124

    Abstract The development of human-robot interaction has been continuously increasing for the last decades. Through this development, it has become simpler and safe interactions using a remotely controlled telepresence robot in an insecure and hazardous environment. The audio-video communication connection or data transmission stability has already been well handled by fast-growing technologies such as 5G and 6G. However, the design of the physical parameters, e.g., maneuverability, controllability, and stability, still needs attention. Therefore, the paper aims to present a systematic, controlled design and implementation of a telepresence mobile robot. The primary focus of this paper is… More >

  • Open Access

    ARTICLE

    Acknowledge of Emotions for Improving Student-Robot Interaction

    Hasan Han1, Oguzcan Karadeniz1, Tugba Dalyan2,*, Elena Battini Sonmez2, Baykal Sarioglu1

    Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 1209-1224, 2023, DOI:10.32604/iasc.2023.030674

    Abstract Robot companions will soon be part of our everyday life and students in the engineering faculty must be trained to design, build, and interact with them. The two affordable robots presented in this paper have been designed and constructed by two undergraduate students; one artificial agent is based on the Nvidia Jetson Nano development board and the other one on a remote computer system. Moreover, the robots have been refined with an empathetic system, to make them more user-friendly. Since automatic facial expression recognition skills is a necessary pre-processing step for acknowledging emotions, this paper More >

  • Open Access

    ARTICLE

    Analysing Various Control Technics for Manipulator Robotic System (Robogymnast)

    Mahmoud Mohamed1,2,*, Bdereddin Abdul Samad1,3, Fatih Anayi1, Michael Packianather1, Khalid Yahya4

    CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 4681-4696, 2023, DOI:10.32604/cmc.2023.035312

    Abstract The Robogymnast is a highly complex, three-link system based on the triple-inverted pendulum and is modelled on the human example of a gymnast suspended by their hands from the high bar and executing larger and larger upswings to eventually rotate fully. The links of the Robogymnast correspond respectively to the arms, trunk, and lower limbs of the gymnast, and from its three joints, one is under passive operation, while the remaining two are powered. The passive top joint poses severe challenges in attaining the smooth movement control needed to operate the Robogymnast effectively. This study More >

  • Open Access

    ARTICLE

    SMINER: Detecting Unrestricted and Misimplemented Behaviors of Software Systems Based on Unit Test Cases

    Kyungmin Sim, Jeong Hyun Yi, Haehyun Cho*

    CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 3257-3274, 2023, DOI:10.32604/cmc.2023.036695

    Abstract Despite the advances in automated vulnerability detection approaches, security vulnerabilities caused by design flaws in software systems are continuously appearing in real-world systems. Such security design flaws can bring unrestricted and misimplemented behaviors of a system and can lead to fatal vulnerabilities such as remote code execution or sensitive data leakage. Therefore, it is an essential task to discover unrestricted and misimplemented behaviors of a system. However, it is a daunting task for security experts to discover such vulnerabilities in advance because it is time-consuming and error-prone to analyze the whole code in detail. Also,… More >

  • Open Access

    ARTICLE

    Real-Time Indoor Path Planning Using Object Detection for Autonomous Flying Robots

    Onder Alparslan*, Omer Cetin

    Intelligent Automation & Soft Computing, Vol.36, No.3, pp. 3355-3370, 2023, DOI:10.32604/iasc.2023.035689

    Abstract Unknown closed spaces are a big challenge for the navigation of robots since there are no global and pre-defined positioning options in the area. One of the simplest and most efficient algorithms, the artificial potential field algorithm (APF), may provide real-time navigation in those places but fall into local minimum in some cases. To overcome this problem and to present alternative escape routes for a robot, possible crossing points in buildings may be detected by using object detection and included in the path planning algorithm. This study utilized a proposed sensor fusion method and an… More >

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