Artificial Life and Robotics最新文献_第2页

Benefit of propellers use against push disturbance for a half-drone wheeled inverted pendulum Prototype 2 半无人机轮式倒立摆样机2螺旋桨对推力扰动的影响

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Artificial Life and Robotics Pub Date : 2026-03-25 DOI: 10.1007/s10015-026-01122-9

Hector Gautier, Shoichi Maeyama

引用次数: 0

Set-based differential evolution with exponential and binomial crossovers for discrete optimization problem 离散优化问题的指数和二项交叉集差分进化

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Artificial Life and Robotics Pub Date : 2026-03-23 DOI: 10.1007/s10015-026-01117-6

Yuto Kuninaga, Michiharu Maeda, Yuta Chikuba

{"title":"Set-based differential evolution with exponential and binomial crossovers for discrete optimization problem","authors":"Yuto Kuninaga, Michiharu Maeda, Yuta Chikuba","doi":"10.1007/s10015-026-01117-6","DOIUrl":"10.1007/s10015-026-01117-6","url":null,"abstract":"<div><p>This paper presents set-based differential evolution with exponential and binomial crossovers for discrete optimization problems. While differential evolution has been traditionally applied to continuous optimization problems, it can be adopted to discrete optimization problem by extending techniques in continuous space into discrete space by employing set-based representation. In our approach, a candidate solution is defined as a crisp set, and all arithmetic operations in mutation are redefined through novel operations. The mutation operator in our algorithm adds two different solutions selected randomly to the current solution and the new solution is constructed probabilistically. For two crossovers, the number of inherited mutant parameters follows an exponential distribution in exponential crossover and that of inherited mutant parameters follows a binomial distribution in binomial crossover. This study investigates exponential and binomial crossover mechanisms within the framework of set-based differential evolution. Specifically, we examine the influence of crossover rate on solution accuracy in traveling salesman problem, conducted in two phases: broad search and narrow search. To demonstrate the effectiveness of our algorithms, we examine numerical experiments and compare results with existing algorithms.</p></div>","PeriodicalId":46050,"journal":{"name":"Artificial Life and Robotics","volume":"31 2","pages":"441 - 456"},"PeriodicalIF":0.8,"publicationDate":"2026-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147938695","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

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Acute effects of acupuncture (contact needle technique) on facial skin hydration and superficial capillary morphology: a pilot pre–post-study 针刺（接触针技术）对面部皮肤水合和浅表毛细血管形态的急性影响：一项试点前后研究

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Artificial Life and Robotics Pub Date : 2026-03-05 DOI: 10.1007/s10015-026-01121-w

Hongyang Li, Aya Komiya, Keiichi Sugata, Osamu Tanno, Keiko Ogawa-Ochiai

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Design of a robotic gripper with two servo motors for infinite wrist rotation and performance evaluation for valve operation 腕部无限旋转双伺服电机机械手设计及阀门操作性能评估

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Artificial Life and Robotics Pub Date : 2026-03-04 DOI: 10.1007/s10015-026-01118-5

Jehun Seo, Rion Sunaoshi, Yoshiaki Yamazaki

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Toward ownership understanding of objects: active question generation with large language model and probabilistic generative model 对对象所有权的理解：基于大语言模型和概率生成模型的主动问题生成

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Artificial Life and Robotics Pub Date : 2026-02-28 DOI: 10.1007/s10015-026-01116-7

Saki Hashimoto, Shoichi Hasegawa, Tomochika Ishikawa, Akira Taniguchi, Yoshinobu Hagiwara, Lotfi El Hafi, Tadahiro Taniguchi

{"title":"Toward ownership understanding of objects: active question generation with large language model and probabilistic generative model","authors":"Saki Hashimoto, Shoichi Hasegawa, Tomochika Ishikawa, Akira Taniguchi, Yoshinobu Hagiwara, Lotfi El Hafi, Tadahiro Taniguchi","doi":"10.1007/s10015-026-01116-7","DOIUrl":"10.1007/s10015-026-01116-7","url":null,"abstract":"<div><p>Robots operating in domestic and office environments must understand object ownership to correctly execute instructions such as “Bring me my cup.” However, ownership cannot be reliably inferred from visual features alone. To address this gap, we propose Active Ownership Learning (ActOwL), a framework that enables robots to actively generate and ask users ownership-related questions. ActOwL employs a probabilistic generative model to select questions that maximize information gain, thereby acquiring ownership knowledge to improve learning efficiency. Additionally, by leveraging commonsense knowledge from large language models (LLMs), objects are pre-classified as either shared or owned, and only owned objects are targeted for questioning. Through experiments in a simulated home environment and a real-world laboratory setting, ActOwL achieved significantly higher ownership clustering accuracy with fewer questions than baseline methods. These findings demonstrate the effectiveness of combining active inference with LLM-guided commonsense reasoning, advancing robots’ ability to acquire ownership knowledge for practical, socially appropriate task execution. The project page is available at https://hashimoto-saki.github.io/ActOwl/.</p></div>","PeriodicalId":46050,"journal":{"name":"Artificial Life and Robotics","volume":"31 2","pages":"389 - 404"},"PeriodicalIF":0.8,"publicationDate":"2026-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s10015-026-01116-7.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147938489","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

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A control strategy for monitoring unknown flood regions by multiple UAVs 多无人机监测未知洪区的控制策略

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Artificial Life and Robotics Pub Date : 2026-02-25 DOI: 10.1007/s10015-026-01119-4

Jie Song, Yang Bai, Mikhail Svinin, Evgeni Magid, Naoki Wakamiya

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Application of multimodal interaction in robotic feeding assistance for individuals with upper limb disabilities 多模态交互在上肢残疾人机器人辅助喂养中的应用

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Artificial Life and Robotics Pub Date : 2026-02-14 DOI: 10.1007/s10015-026-01120-x

Fei Liu, Zhi Li, YuXin Sun, Mingyue Hu

{"title":"Application of multimodal interaction in robotic feeding assistance for individuals with upper limb disabilities","authors":"Fei Liu, Zhi Li, YuXin Sun, Mingyue Hu","doi":"10.1007/s10015-026-01120-x","DOIUrl":"10.1007/s10015-026-01120-x","url":null,"abstract":"<div><p>Robotic feeding systems can restore autonomy for individuals with upper limb impairments; however, most existing solutions rely on unimodal perception and rigid control interfaces, which limit adaptability and real-time performance. This study presents a multimodal feeding robot that integrates large-model-based speech understanding, lightweight visual perception, and smooth motion planning. The visual module employs an improved YOLOv8n architecture optimized through a three-stage process of LAMP pruning for compression, fine-tuning for recovery, and BCKD-based knowledge distillation for performance enhancement. Compared with the baseline YOLOv8n, the proposed model achieves improvements of + 1.9% in mAP@0.5 and + 2.0% in mAP@0.5:0.95, while reducing model size from 6.3 MB to 2.7 MB, computational cost from 8.1 GFLOPs to 3.2 GFLOPs, and parameters from 3.0 million to 1.2 million, resulting in an inference speed increase from 27 to 42 FPS. A 3–5–3 segmented polynomial trajectory ensures smooth insert–lift–transfer motions toward a fixed mouth position, maintaining continuous velocity and acceleration profiles. Across 20 consecutive feeding cycles involving three food types (watermelon, Hami melon, and sausage), the system achieved a 100% success rate, with no failures observed during spearing or delivery. These results demonstrate that the proposed multimodal and lightweight feeding framework enables accurate perception, efficient control, and natural human–robot collaboration, thereby providing a practical pathway toward autonomous assistive mealtime systems.</p></div>","PeriodicalId":46050,"journal":{"name":"Artificial Life and Robotics","volume":"31 3","pages":"711 - 720"},"PeriodicalIF":0.8,"publicationDate":"2026-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148695513","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

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Floating object removal in underwater ROV video images using segment anything model and generative image in-painting 基于分段任意模型和生成图像绘图的水下ROV视频图像漂浮物去除

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Artificial Life and Robotics Pub Date : 2026-02-01 DOI: 10.1007/s10015-025-01100-7

Hiroki Takahashi, Toru Kato, Meguru Yamashita, Akio Doi, Takashi Imabuchi

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Intersection traffic control with individual virtual wall and deceleration avoidance in a dynamic traffic flow environment 动态交通流环境下具有独立虚拟墙和减速规避的交叉口交通控制

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Artificial Life and Robotics Pub Date : 2026-01-30 DOI: 10.1007/s10015-025-01108-z

Yuki Itoh, Tenta Suzuki, Kaito Kumagae, Mao Tobisawa, Tomohiro Harada, Johei Matsuoka, Kiyohiko Hattori

{"title":"Intersection traffic control with individual virtual wall and deceleration avoidance in a dynamic traffic flow environment","authors":"Yuki Itoh, Tenta Suzuki, Kaito Kumagae, Mao Tobisawa, Tomohiro Harada, Johei Matsuoka, Kiyohiko Hattori","doi":"10.1007/s10015-025-01108-z","DOIUrl":"10.1007/s10015-025-01108-z","url":null,"abstract":"<div><p>With the advancement of machine learning and sensor technology, along with information sharing via vehicle-to-vehicle communication, overall optimization of traffic control focused on autonomous vehicles is becoming feasible. As an intersection traffic control method in a fully autonomous driving society, intersection control using Virtual Walls (VW), which differs from conventional optical traffic signals, has been proposed. VWs function as virtual obstacles and dynamically control vehicle routes to achieve safe intersection passage for autonomous vehicles. However, existing VW methods have two limitations: (1) complete avoidance of inter-vehicle collisions is difficult, and (2) they have only been evaluated in static environments with a fixed number of vehicles and fixed initial positions, limiting their practicality. To address these issues, this research proposes two functional extensions. First, we propose an individual VW placement optimization algorithm that corresponds to combinations of vehicle generation positions and destinations in a dynamic traffic flow environment where vehicles are continuously generated. Second, we introduce a Deceleration Avoidance function based on vehicle trajectory prediction to achieve collision avoidance through minimal speed adjustments in situations that are difficult to address through route design using VW control alone. Simulation evaluation in both static and dynamic traffic flow environments confirmed that the proposed method significantly reduces the number of collisions compared to conventional methods and achieves effective intersection control even in dynamic traffic flow environments.</p></div>","PeriodicalId":46050,"journal":{"name":"Artificial Life and Robotics","volume":"31 1","pages":"239 - 253"},"PeriodicalIF":0.8,"publicationDate":"2026-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147342756","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

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Evolutionary multi-objective optimization with the heuristic solver for multiple traveling salesman problem 多旅行商问题的启发式进化多目标优化

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Artificial Life and Robotics Pub Date : 2026-01-28 DOI: 10.1007/s10015-025-01098-y

Yoshiaki Katada, Shinya Watanabe, Kazuhiro Ohkura

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