Three-dimensional path planning refers to determining an optimal path in a three-dimensional space with obstacles, so that the path is as close to the target location as possible, while meeting some other constraints, including distance, altitude, threat area, flight time, energy consumption, and so on. Although the bald eagle search algorithm has the characteristics of simplicity, few control parameters, and strong global search capabilities, it has not yet been applied to complex three-dimensional path planning problems. In order to broaden the application scenarios and scope of the algorithm and solve the path planning problem in three-dimensional space, we present a study where five three-dimensional geographical environments are simulated to represent real-life unmanned aerial vehicles flying scenarios. These maps effectively test the algorithm's ability to handle various terrains, including extreme environments. The experimental results have verified the excellent performance of the BES algorithm, which can quickly, stably, and effectively solve complex three-dimensional path planning problems, making it highly competitive in this field.
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http://dx.doi.org/10.3934/mbe.2024127 | DOI Listing |
Injury
January 2025
Department of Orthopaedic Surgery, Cedars - Sinai Medical Center, Los Angeles, CA, USA. Electronic address:
Objectives: The purpose of this study is to determine what demographic and anatomical variables affect successful placement of a superior medullary ramus screw, and how they affect the maximal diameter of that screw.
Methods: Design: Prognostic Level IV SETTING: Level I Trauma Center Patients/Participants: Two hundred consecutive patients underwent computed tomography (CT) of the pelvis. We included those patients aged 18 and older without osseous injury or abnormalities precluding measurement.
Nutrients
January 2025
Department of Psychobiology and Methodology, Universitat Autònoma de Barcelona, 08193 Barcelona, Spain.
Background-objectives: Multiple dynamic interacting factors contribute to the presence and progression of eating disorders (ED). Empirical research has provided mixed findings regarding the mechanisms explaining the contribution of body mass index (BMI) to the diverse ED endophenotypes. The present study aims to evaluate the underlying processes (direct and indirect effects) contributing to BMI and ED severity, considering the contribution of multiple neuropsychological constructs.
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January 2025
College of Resource Environmental and Safety Engineering, University of South China, Hengyang 421001, China.
To solve the issue of inconvenient and dangerous manual operation during the installation and removal of the main pipe plugging plate in the steam generator in nuclear power plants, a ten-degree-of-freedom plugging robot was designed in the present study that includes a collaborative robotic arm coupled with a servo electric cylinder. By establishing a joint coordinate system for the robot model, a D-H parameter model for the plate plugging robot was established, and the forward and inverse kinematics were solved. The volume level approximate convex decomposition algorithm was used to fit the steam generator model with a convex packet, and an experimental simulation platform was constructed.
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January 2025
School of Biomedical Engineering and Imaging Sciences, King's College London, London SE1 7EH, UK.
Ultrasound imaging is widely valued for its safety, non-invasiveness, and real-time capabilities but is often limited by operator variability, affecting image quality and reproducibility. Robot-assisted ultrasound may provide a solution by delivering more consistent, precise, and faster scans, potentially reducing human error and healthcare costs. Effective force control is crucial in robotic ultrasound scanning to ensure consistent image quality and patient safety.
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January 2025
Department of Product & Systems Design Engineering, University of the Aegean, 84100 Syros, Greece.
This paper addresses the complex problem of multi-goal robot navigation, framed as an NP-hard traveling salesman problem (TSP), in environments with both static and dynamic obstacles. The proposed approach integrates a novel path planning algorithm based on the Bump-Surface concept to optimize the shortest collision-free path among static obstacles, while a Genetic Algorithm (GA) is employed to determine the optimal sequence of goal points. To manage static or dynamic obstacles, two fuzzy controllers are developed: one for real-time path tracking and another for dynamic obstacle avoidance.
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