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  • Open Access

    ARTICLE

    Research on Adaptive Reward Optimization Method for Robot Navigation in Complex Dynamic Environment

    Jie He, Dongmei Zhao, Tao Liu*, Qingfeng Zou, Jian’an Xie

    CMC-Computers, Materials & Continua, Vol.84, No.2, pp. 2733-2749, 2025, DOI:10.32604/cmc.2025.065205 - 03 July 2025

    Abstract Robot navigation in complex crowd service scenarios, such as medical logistics and commercial guidance, requires a dynamic balance between safety and efficiency, while the traditional fixed reward mechanism lacks environmental adaptability and struggles to adapt to the variability of crowd density and pedestrian motion patterns. This paper proposes a navigation method that integrates spatiotemporal risk field modeling and adaptive reward optimization, aiming to improve the robot’s decision-making ability in diverse crowd scenarios through dynamic risk assessment and nonlinear weight adjustment. We construct a spatiotemporal risk field model based on a Gaussian kernel function by combining… More >

  • Open Access

    ARTICLE

    Pathfinder: Deep Reinforcement Learning-Based Scheduling for Multi-Robot Systems in Smart Factories with Mass Customization

    Chenxi Lyu1, Chen Dong1, Qiancheng Xiong1, Yuzhong Chen1, Qian Weng1,*, Zhenyi Chen2

    CMC-Computers, Materials & Continua, Vol.84, No.2, pp. 3371-3391, 2025, DOI:10.32604/cmc.2025.065153 - 03 July 2025

    Abstract The rapid advancement of Industry 4.0 has revolutionized manufacturing, shifting production from centralized control to decentralized, intelligent systems. Smart factories are now expected to achieve high adaptability and resource efficiency, particularly in mass customization scenarios where production schedules must accommodate dynamic and personalized demands. To address the challenges of dynamic task allocation, uncertainty, and real-time decision-making, this paper proposes Pathfinder, a deep reinforcement learning-based scheduling framework. Pathfinder models scheduling data through three key matrices: execution time (the time required for a job to complete), completion time (the actual time at which a job is finished),… More >

  • Open Access

    ARTICLE

    Methods for the Segmentation of Reticular Structures Using 3D LiDAR Data: A Comparative Evaluation

    Francisco J. Soler Mora1,*, Adrián Peidró Vidal1, Marc Fabregat-Jaén1, Luis Payá Castelló1,2, Óscar Reinoso García 1,2

    CMES-Computer Modeling in Engineering & Sciences, Vol.143, No.3, pp. 3167-3195, 2025, DOI:10.32604/cmes.2025.064510 - 30 June 2025

    Abstract Reticular structures are the basis of major infrastructure projects, including bridges, electrical pylons and airports. However, inspecting and maintaining these structures is both expensive and hazardous, traditionally requiring human involvement. While some research has been conducted in this field of study, most efforts focus on faults identification through images or the design of robotic platforms, often neglecting the autonomous navigation of robots through the structure. This study addresses this limitation by proposing methods to detect navigable surfaces in truss structures, thereby enhancing the autonomous capabilities of climbing robots to navigate through these environments. The paper… More >

  • Open Access

    ARTICLE

    Feasibility and short-term outcomes of robotic distal ureteroureterostomy for benign obstruction

    Jonathan A. Seaman*, Rita Palanjian, John Fitzgerald, Kyle McCormick, Joel Funk, Sunchin Kim

    Canadian Journal of Urology, Vol.32, No.3, pp. 181-187, 2025, DOI:10.32604/cju.2025.064047 - 27 June 2025

    Abstract Introduction: Distal ureteral obstruction has classically been managed by ureteroneocystostomy (UNC). The feasibility and success of robotic primary ureteroureterostomy (UU) for benign obstruction appears promising with several benefits over UNC but is poorly studied. Robotic repair offers superior visualization and precision, allowing for minimal ureteral dissection. Here we report on our experience and short-term outcomes. Materials and Methods: We identified patients who underwent robotic distal ureteroureterostomy for benign distal ureteral obstruction at our institution from 2020–2024. Etiology, stricture length, and post-operative outcomes were recorded. All patients had renal ultrasound (US), diuretic renography, or cross-sectional imaging within… More >

  • Open Access

    ARTICLE

    Robotic-assisted super-extended pelvic lymph node dissection for prostate cancer: safety and pathologic findings

    Ryan Daigle1, Ilene Staff2, Joseph Tortora2, Tara McLaughlin Proto3,*, Kevin Pinto3, Rosa Negron2, Jonathan Earle4, Joseph Wagner,3

    Canadian Journal of Urology, Vol.32, No.3, pp. 189-198, 2025, DOI:10.32604/cju.2025.063773 - 27 June 2025

    Abstract Introduction: We examined the pathology and safety outcomes associated with the extent of pelvic lymph node dissection in patients with high-risk prostate cancer undergoing radical prostatectomy. Materials and Methods: We retrospectively identified men with prostate cancer who underwent robot-assisted radical prostatectomy with pelvic lymph node dissection between May 2016 and September 2021. Cases were categorized using Current Procedural Terminology (CPT) codes (38571) for extended lymph node dissection and super-extended lymph node dissection (38572). Using logistic regression, we compared the groups on a number of factors, including recurrence. Results: Super-extended lymph node dissection had significantly higher median… More >

  • Open Access

    ARTICLE

    Obstacle Avoidance Path Planning for Delta Robots Based on Digital Twin and Deep Reinforcement Learning

    Hongxiao Wang1, Hongshen Liu1, Dingsen Zhang1,*, Ziye Zhang1, Yonghui Yue1, Jie Chen2

    CMC-Computers, Materials & Continua, Vol.83, No.2, pp. 1987-2001, 2025, DOI:10.32604/cmc.2025.060384 - 16 April 2025

    Abstract Despite its immense potential, the application of digital twin technology in real industrial scenarios still faces numerous challenges. This study focuses on industrial assembly lines in sectors such as microelectronics, pharmaceuticals, and food packaging, where precision and speed are paramount, applying digital twin technology to the robotic assembly process. The innovation of this research lies in the development of a digital twin architecture and system for Delta robots that is suitable for real industrial environments. Based on this system, a deep reinforcement learning algorithm for obstacle avoidance path planning in Delta robots has been developed, More >

  • Open Access

    REVIEW

    Gait Planning, and Motion Control Methods for Quadruped Robots: Achieving High Environmental Adaptability: A Review

    Sheng Dong*, Feihu Fan, Yinuo Chen, Shangpeng Guo, Jiayu Liu

    CMES-Computer Modeling in Engineering & Sciences, Vol.143, No.1, pp. 1-50, 2025, DOI:10.32604/cmes.2025.062113 - 11 April 2025

    Abstract Legged robots have always been a focal point of research for scholars domestically and internationally. Compared to other types of robots, quadruped robots exhibit superior balance and stability, enabling them to adapt effectively to diverse environments and traverse rugged terrains. This makes them well-suited for applications such as search and rescue, exploration, and transportation, with strong environmental adaptability, high flexibility, and broad application prospects. This paper discusses the current state of research on quadruped robots in terms of development status, gait trajectory planning methods, motion control strategies, reinforcement learning applications, and control algorithm integration. It More >

  • Open Access

    ARTICLE

    Enhancing Emotional Expressiveness in Biomechanics Robotic Head: A Novel Fuzzy Approach for Robotic Facial Skin’s Actuators

    Nguyen Minh Trieu, Nguyen Truong Thinh*

    CMES-Computer Modeling in Engineering & Sciences, Vol.143, No.1, pp. 477-498, 2025, DOI:10.32604/cmes.2025.061339 - 11 April 2025

    Abstract In robotics and human-robot interaction, a robot’s capacity to express and react correctly to human emotions is essential. A significant aspect of the capability involves controlling the robotic facial skin actuators in a way that resonates with human emotions. This research focuses on human anthropometric theories to design and control robotic facial actuators, addressing the limitations of existing approaches in expressing emotions naturally and accurately. The facial landmarks are extracted to determine the anthropometric indicators for designing the robot head and is employed to the displacement of these points to calculate emotional values using Fuzzy… More >

  • Open Access

    ARTICLE

    Improved Bidirectional JPS Algorithm for Mobile Robot Path Planning in Complex Environments

    Zhaohui An, Changyong Li*, Yong Han, Mengru Niu

    CMC-Computers, Materials & Continua, Vol.83, No.1, pp. 1347-1366, 2025, DOI:10.32604/cmc.2025.059037 - 26 March 2025

    Abstract This paper introduces an Improved Bidirectional Jump Point Search (I-BJPS) algorithm to address the challenges of the traditional Jump Point Search (JPS) in mobile robot path planning. These challenges include excessive node expansions, frequent path inflexion points, slower search times, and a high number of jump points in complex environments with large areas and dense obstacles. Firstly, we improve the heuristic functions in both forward and reverse directions to minimize expansion nodes and search time. We also introduce a node optimization strategy to reduce non-essential nodes so that the path length is optimized. Secondly, we… More >

  • Open Access

    ARTICLE

    Continuous Monitoring of Multi-Robot Based on Target Point Uncertainty

    Guodong Yuan1,*, Jin Xie2

    Journal on Artificial Intelligence, Vol.7, pp. 1-16, 2025, DOI:10.32604/jai.2025.061437 - 14 March 2025

    Abstract This paper addresses the problem of access efficiency in multi-robot systems to the monitoring area. A distributed algorithm for multi-robot continuous monitoring, based on the uncertainty of target points, is used to minimize the uncertainty and instantaneous idle time of all target points in the task domain, while maintaining a certain access frequency to the entire task domain at regular time intervals. During monitoring, the robot uses shared information to evaluate the cumulative uncertainty and idle time of the target points, and combines the update list collected from adjacent target points with a utility function More >

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