Опубликована: Июнь 18, 2024
Язык: Английский
Engineering Science and Technology an International Journal, Год журнала: 2025, Номер 62, С. 101942 - 101942
Опубликована: Янв. 24, 2025
Язык: Английский
Процитировано
1
AIAA SCITECH 2022 Forum, Год журнала: 2025, Номер unknown
Опубликована: Янв. 3, 2025
Язык: Английский
Процитировано
0
Опубликована: Июнь 7, 2024
The rapid growth of robot applications across various sectors, such as agriculture, disaster management, and package delivery, has led to an increased demand for efficient safe multi-robot path planning methods. Existing solutions face significant challenges in simultaneously paths multiple robots, maintaining distances from obstacles other dealing with local minima issues. In this research, potential field-based method nature-inspired algorithm is proposed overcome these limitations, resulting competent, short, time-saving even complex environments. Our algorithms consider the simultaneous robots located at different locations while ensuring a distance robots. Multi-Robot multi-task allocation developed optimize time. A scheme avoid static dynamic effectively. Additionally, our approach solves problem simulated annealing algorithm, which supplement navigator. Finally, generating short time-efficient paths, By augmenting efficiency safety operations, work will contribute reduction operational expenses, enhancement productivity, minimization accident risks.
Язык: Английский
Процитировано
0
Опубликована: Авг. 4, 2024
Abstract Optimizing robot path planning, a key domain within computational intelligence and robotics, is gaining significant prominence today. Graph-based models for planning optimization represent highly impactful advancement in both research educational aspects of intelligence. Nonetheless, teaching this subject curriculum challenging task. In general, graph-based techniques are versatile extensively utilized, offering structured approach to analyze intricate environments determine efficient safe paths. Their adaptability diverse types positions them as fundamental tools the fields robotics. study, we introduce pedagogical that integrates sparrow-dissection scaffolding (SDS) with active learning ongoing project-based methods. This aims assist students design, implementation, debugging, operation planning. We teach visibility classroom provide corresponding source code. Students expected review adapt provided code order apply method their tasks. our Computational Intelligence course graduate students, model along its code, serving foundation dissect understand method. collaboratively guide revising customizing specific needs. As students' progress through series assigned projects centered on application method, they gradually gain independence eventually complete own. Throughout course, given set require employ methods actively seek feedback after each project assess development, these Our promotes learning, encouraging participate, ask questions, engage instructor peers explore effective optimizing involvement greatly enhances comprehension matter. efficacy milestone assignments, presentations, interactive activities. also gather student concepts before project, well input development neural network models, accomplished revision initial strategies, underpinned by integrated approaches, closely linked outcomes course. connection established an in-depth analysis involving When evaluating overall effectiveness, integrate data information from evaluation system. The combination insights underscores effectiveness high quality achieved approach, which combines 'sparrow-dissection' pedagogies.
Язык: Английский
Процитировано
0
Опубликована: Авг. 4, 2024
Abstract Nature-inspired intelligence, an integral component of computational intelligence curriculum. The integration nature-inspired methodologies with robotics has become increasingly prominent in research and education. Among its diverse applications, the utilization these methods for optimizing robot path planning enhancing motion control stands out as a significant advancement field intelligence. However, incorporation concepts into curricula presents noteworthy pedagogical challenge. draws inspiration from behaviors strategies observed natural systems, including animals, plants, ecological processes. These approaches strive to create algorithms that are both efficient adaptive by mimicking principles found nature. In this research, pedagogy sparrow-dissection scaffolding (SDS) integrated flipped learning milestone on-going project-based method is developed assist students comprehend, create, implement models optimization control. our graduate-level Computational Intelligence curriculum, we introduce various such particle swarm (PSO), genetic (GA), bat (BA). provided along their source codes, serving 'sparrow' dissect explore how can be applied optimize planning. Working collaboratively students, guide them through process revising customizing codes purpose Integrating approach multiple milestones establish dynamic captivating environment. Within classroom model, receive algorithm materials before class, reading assignments online resources. This pre-class preparation empowers review at own convenience, enabling build solid foundation methods. ongoing projects, pedagogy, serve dual purpose. They not only aim improve students' comprehension but also nurture sharpen problem-solving, critical thinking, problem analysis skills. During in-class time, utilize activities discuss projects. We provide project guidelines objectives, organize groups collaborate on projects related elaborately design practice exercises after each lecture. hybrid take ownership algorithms, problem-solving skills connect It promotes active engagement, collaborative learning, making educational experience more meaningful students. Based performance homework assignments, Q&A sessions, exams, self-assessment surveys, feedback official university course evaluation, comparison instructor's other teaching experiences, adopted was highly effective facilitating models. final assessment evaluation innovative delivering education, informed valuable insights, further confirms effectiveness.
Язык: Английский
Процитировано
0
Biomimetic Intelligence and Robotics, Год журнала: 2024, Номер unknown, С. 100189 - 100189
Опубликована: Окт. 1, 2024
Язык: Английский
Процитировано
0
Опубликована: Июнь 18, 2024
Язык: Английский
Процитировано
0