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swarm robotics for collaborative object transport using a pushing strategy

EXPERT SYSTEMS WITH APPLICATIONS 2025年 271卷

作者： Nedjah, Nadia Ferreira, Gustavo Bueno Mourelle, Luiza de Macedo Univ Estado Rio De Janeiro Engn Fac Dept Elect Engn & Telecommun Rio De Janeiro RJ Brazil Univ Estado Rio De Janeiro Engn Fac Dept Syst Engn & Computat Rio De Janeiro RJ Brazil

Coordinated object transport by a robotic swarm is useful when an object is too large or heavy for one robot to handle. Cooperative transport requires the robots to synchronize their pushing efforts for successful movement. This work introduces anew algorithm for Cooperative Object Transport by Pushing (COTP), which operates in four stages. First, robots search for the object. When one robot finds it, it calls others to join. Next, each robot calculates and moves to its designated position behind the object. Once positioned, the robots push and reposition in turns to keep the object on its path until it reaches the destination. For object search, two strategies are explored: random search and a method inspired by ant colonies, where robots deposit pheromones on the traversed paths. The COTP algorithm is tested on GRITSBot robots in the Robotarium platform simulator. The study evaluates the performance of the two search methods, robot positioning during pushing, number of robots involved, and object size and weight. Key findings of this investigation are four-fold: (i) The ant-inspired search method achieves shorter paths than random search, with route length reductions of 6.7% when only forward movement is allowed and 52.35% with both forward and backward movements. (ii) Positioning the robots at maximum angles minimizes path length errors, reducing error by an average of 75.76%. (iii) Using more robots than the minimum needed speeds up transport, reducing time by up to 829.77 s. (iv) The required robot number should be proportional to the object's size and weight to ensure efficient transport. This study highlights that strategic search methods, optimal positioning, and increased robot numbers significantly improve object transport efficiency.

关键词： Cooperative transport swarm robotics swarm intelligence Artificial foraging

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BEE-SLAM: A 65-nm 17.96-TOPS/W Location-Sharing-Based Multi-Agent Neuromorphic SLAM Accelerator for swarm robotics

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IEEE JOURNAL OF SOLID-STATE CIRCUITS 2025年第3期60卷 963-976页

作者： Lee, Jaehyun Choi, Dong-Gu Kim, Gain Song, Minyoung Yoon, Jong-Hyeok Daegu Gyeongbuk Inst Sci & Technol DGIST Dept Elect Engn & Comp Sci Daegu 42988 South Korea

Multi-agent (MA) simultaneous localization and mapping (SLAM) has been rigorously explored to enhance map accuracy in swarm robotics. Although centralized MA SLAM systems, which depend on a server for complex computations in map optimization, have been extensively studied, the circuit-domain approaches to decentralized MA SLAM systems are still limited due to challenges such as limited memory capacity and security vulnerabilities in wireless inter-agent data transmission. Thus, we propose a BEE-SLAM accelerator, a location-sharing MA neuromorphic SLAM accelerator inspired by bee communication for decentralized MA SLAM systems. The location-sharing-based MA error correction (MAEC) is employed to attain accurate map results without loop closure with a 94.81% reduced number of operations compared to the global map-based MA SLAM. In addition, a 7 x 7 pulsewidth modulation (PWM)-based hybrid mixed-signal/digital pose-cell (HY-PC) array with pseudo pose cells (PPCs) achieves 2.04 x energy efficiency compared to the oscillatory pose-cell array. The test chip fabricated in a 65-nm CMOS technology achieves a peak energy efficiency of 17.96 TOPS/W under 350 x 450 m outdoor exploration.

关键词： Simultaneous localization and mapping Trajectory Humanities Flowering plants Accelerated aging Visualization Security Neuromorphics Error correction swarm robotics Bee communication location sharing neuromorphic system simultaneous localization and mapping (SLAM) swarm robotics

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Tube RRT*: Efficient Homotopic Path Planning for swarm robotics Passing-Through Large-Scale Obstacle Environments

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IEEE robotics AND AUTOMATION LETTERS 2025年第3期10卷 2247-2254页

作者： Mao, Pengda Lv, Shuli Quan, Quan Beihang Univ Sch Automat Sci & Elect Engn Beijing 100191 Peoples R China

Recently, the concept of homotopic trajectory planning has emerged as a novel solution to navigation in large-scale obstacle environments for swarm robotics, offering a wide range of applications. However, it lacks an efficient homotopic path planning method in large-scale obstacle environments. This letter introduces Tube RRT*, an innovative homotopic path planning method that builds upon and improves the Rapidly-exploring Random Tree (RRT) algorithm. Tube RRT* is designed to efficiently generate homotopic paths belonging to the same homotopy class and simultaneously considers gap volume and path length to mitigate swarm congestion and enable agile navigation. Through comprehensive simulations and experiments, the effectiveness of Tube RRT* is validated.

关键词： swarm robotics Navigation Costs Trajectory planning Trajectory Robot kinematics Three-dimensional displays Planning Collision avoidance Topology Motion and path planning multi-robot systems homotopic path virtual tube

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Quantum computing for swarm robotics: a local-to-global approach

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PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES 2025年第2289期383卷 20240139页

作者： Mannone, Maria Seidita, Valeria Chella, Antonio Natl Res Council CNR ICAR Palermo Italy Ca Foscari Univ Venice Dipartimento Sci Mol & Nanosistemi DSMN Venice Italy Ca Foscari Univ Venice European Ctr Living Technol ECLT Venice Italy Univ Potsdam Inst Phys & Astron Potsdam Germany Univ Palermo Dept Engn Palermo Italy

Quantum computing is a branch of computer science derived from the fundamental laws of quantum mechanics, such as state superposition, multi-value logic and destructive measure. An open challenge in itself is to re-think in quantum terms classic problems and solving techniques. Another nature-inspired field is the development of swarm-based robotic applications, where the challenge is catching the fundamental laws governing swarm dynamics, such as pattern formation and target reaching. Here, we review some recent approaches on swarm dynamics, the organizational rules of which are formalized according to quantum computing. In this way, the shades of probability in decision-making for multiple-robot systems can be expressed according to the multi-value logic underlying quantum computing. In our review, specific quantum circuits are sketched to give an idea of how these problems have been faced in computational terms. The article is enriched by references to sonification, a strategy adding one more sensory dimension to data representation, a human-friendly tool to navigate the complexity of swarm-robotic movements in a given *** article is part of the theme issue 'The road forward with swarm systems'.

关键词： swarm robotics quantum computing decision process

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Energy Efficiency Optimization in swarm robotics for Smart Photovoltaic Monitoring

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ENERGIES 2025年第7期18卷

作者： Ziouzios, Dimitris Baras, Nikolaos Dasygenis, Minas Karayannis, Vayos Tsanaktsidis, Constantinos Univ Western Macedonia Dept Chem Engn ZEP Campus Kozani 50100 Greece Univ Western Macedonia Dept Elect & Comp Engn ZEP Campus Kozani 50100 Greece

Photovoltaic park (PV) and power generator monitoring is a crucial activity that calls for effective coverage path planning. Artificial intelligence and particularly swarm robotics have brought new methods to tasks such as coverage path planning by having multiple robots work together to cover a specific area. Nonetheless, enhancing energy efficiency in these systems continues to be a crucial obstacle, particularly with the growing focus on sustainability. This research investigates techniques to enhance energy efficiency in swarm robotics, focusing on coverage path planning assignments. The proposed approach merges advanced swarm robotics algorithms with energy-efficient methods to reduce power consumption while still ensuring effective coverage. Thorough simulations in simulated environments of Western Macedonia assess the efficiency of the proposed approach. Even though the proposed approach has a longer convergence time compared to a generic ACO approach, the findings of the simulations indicate that the MOACO approach has substantial enhancements up to 22% in path travel time, in terms of solution quality and energy consumption metrics. The findings of the present work offer valuable insights into the design of sustainable robotic systems and underscore the potential of swarm robotics in achieving efficient coverage path planning. This study adds to the overall objective of creating eco-friendly technologies in robotics, leading to upcoming advancements in the industry.

关键词： energy optimization artificial intelligence (AI) swarm robotics photovoltaic (PV) monitoring coverage path planning

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Gazing Preference Induced Controllable Milling Behavior in swarm robotics

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IEEE robotics AND AUTOMATION LETTERS 2025年第6期10卷 5769-5776页

作者： Zhou, Yongjian Song, Jintao Liu, Tong Peng, Xingguang Northwestern Polytech Univ Sch Marine Sci & Technol Xian 710072 Peoples R China Xian Univ Architecture & Technol Sch Informat & Control Engn Xian 710055 Peoples R China

Milling is a collective behavior that is useful in a variety of real scenarios, but how to regulate milling behavior simply and efficiently is still a challenging problem. This letter introduces a novel method for controlling milling behavior in real-world robots, where both the direction and radius of the milling pattern can be continuously adjusted by tuning a single parameter. Inspired by visual attention mechanisms, the proposed model introduces the concept of gazing preference. That is, the robot will prefer to choose a neighbor in a particular direction for interaction, which in turn creates a force that deviates from the direction of velocity and leads to the milling behavior. Additionally, a potential function ensures swarm cohesion and prevents collisions through simulated repulsive and attractive forces. Simulations and experiments involving up to 50 robots demonstrate that adjusting the gazing preference parameter enables seamless control of the rotation direction and fine-tuning of the milling pattern's angular velocity and radius. Overall, this letter provides a straightforward and effective approach for designing controlled milling behavior in swarm robotics.

关键词： Milling Robots swarm robotics Collision avoidance Robot sensing systems Visualization Probability density function Mobile robots Force Angular velocity Collective behavior milling gazing preference swarm robots

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Collaborative swarm robotics for sustainable environment monitoring and exploration: Emerging trends and research progress

ENERGY NEXUS

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ENERGY NEXUS 2025年 17卷

作者： Khaldi, Belkacem Harrou, Fouzi Sun, Ying Ecole Super Informat 08 Mai 1945 LabRI SBA Lab BP 73Bur poste EL WIAM Sidi Bel Abbes Algeria King Abdullah Univ Sci & Technol KAUST Comp Elect & Math Sci & Engn CEMSE Div Thuwal 239556900 Saudi Arabia

This study explores the application of swarm robotics and swarm and evolutionary computing techniques in environmental management and sustainability, a highly specific and increasingly demanding niche research area. Through a bibliometric analysis of two collections of peer-reviewed papers, key trends and emerging research areas are identified. The first collection, comprising approximately 450 papers, focuses on specific applications of swarm robotics systems in environmental use cases, including swarms of UAVs, AUVs, and USVs, particularly in tasks such as ecological monitoring, agricultural management, and disaster response. This analysis highlights essential keyword clusters, with ``ecological restoration" emerging as a significant topic, and ``agricultural robots" and ``remote sensing" as active frontiers. Building on this analysis, eight directions are proposed to address environmental challenges across five categories. The second collection, consisting of around 198 papers, examines the different swarm and evolutionary computing algorithms employed in this niche area, identifying ten significant research clusters. Notably, the ``secure incentive mechanism" is a trending area, emphasizing the development of reliable and secure cooperative multi-robot systems. Recent methods in this cluster utilize deep reinforcement learning and heuristic algorithms to enhance cooperation efficiency. Five potential directions categorized into two main groups are explored to address security and reliability challenges within swarm robot systems in environmental tasks. The findings underscore the critical role of swarm robotics in environment-focused tasks such as ecosystem recovery and the importance of secure cooperation mechanisms, paving the way for advancements in agriculture, resource management, intelligent infrastructure, and urban systems.

关键词： Environmental sustainability swarm robotics Bibliometric analysis Ecological restoration Agricultural robot Secure incentive mechanism

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Nature-Inspired Solutions for Sustainable Mining: Applications of NIAs, swarm robotics, and Other Biomimicry-Based Technologies

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BIOMIMETICS 2025年第3期10卷 181页

作者： Tan, Joven Melkoumian, Noune Harvey, David Akmeliawati, Rini Univ Adelaide Sch Chem Engn Discipline Min & Petr Engn Adelaide 5005 Australia Univ Adelaide Sch Elect & Mech Engn Adelaide 5005 Australia

Environmental challenges, high safety risks and operational inefficiencies are some of the issues facing the mining sector. The paper offers an integrated viewpoint to address these issues by combining swarm robotics, nature-inspired algorithms (NIAs) and other biomimicry-based technologies into a single framework. It presents a systematic classification of each methodology, emphasizing their key advantages and disadvantages as well as considering real-life mining application scenarios, including hazard detection, autonomous transportation and energy-efficient drilling. Case studies are citied to demonstrate how these methodologies work together, and an extensive comparison table considering their applications at mines, such as Boliden, Diavik Diamond Mine, Olympic Dam and others, presents a summary of their scalability and practicality. This paper highlights future directions such as multi-robot coordination and hybrid NIAs, to improve operational resilience and sustainability. It also provides a broad overview of biomimicry and critically examines unresolved issues like real-time adaptation, parameter tuning and mechanical wear. The paper aims to offer a comprehensive insight into using bio-inspired models to enhance mining efficiency, safety and environmental management, while proposing a road map for resolving the issues that continue to be a hurdle for wide adaptation of these technologies in the mining industry.

关键词： biomimicry nature-inspired algorithms swarm robotics mining automation collective intelligence sustainable mining

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Accelerating Resource-Constrained swarm robotics With Cone-Based Loop Closure and 6G Communication

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IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS 2025年

作者： Iqbal, Muddesar Memon, Azam Rafique Almakhles, Dhafer J. Prince Sultan Univ Coll Engn Renewable Energy Lab Riyadh 12435 Saudi Arabia

Loop closure detection, a critical component of Simultaneous Localization and Mapping (SLAM) systems, can be computationally intensive, particularly in swarm robotics where coordination among multiple agents is essential. Traditional SLAM methods often involve comparing each frame with all previous frames, leading to performance bottlenecks, especially on battery-operated or resource-constrained devices. This leaves little room for other critical tasks, such as continuous coordination and information sharing among swarm robots, which require swift execution to perform effectively. This paper introduces a novel cone-based approach to streamline loop closure detection, significantly reducing the computational burden and improving system efficiency. By limiting frame comparisons to a predefined region, our method accelerates SLAM algorithms, enabling more efficient coordination and exploration among swarm robots. The approach is particularly advantageous for resource-constrained devices and battery-powered platforms operating in dynamic environments. The need for millisecond-level response times in swarm robotic tasks require the integration of 6G networks for seamless communication and coordination. Experimental results demonstrate the effectiveness of the cone-based method in enhancing loop closure accuracy while minimizing computational overhead. This makes it a valuable tool for advancing swarm robotic applications, particularly in 6G-enabled environments where real-time coordination and efficiency are paramount.

关键词： Robot kinematics Simultaneous localization and mapping swarm robotics Real-time systems Trajectory Navigation Accuracy 6G mobile communication Collaboration Scalability Autonomous vehicles 6G networks simultaneous localization and mapping (SLAM) swarm robotics loop closure detection

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Coordination Frameworks for IoT-Driven swarm robotics Communication

Coordination Frameworks for IoT-Driven Swarm Robotics Commun...

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Machine Learning and Autonomous Systems (ICMLAS), International Conference on

作者： Ayush Kumar Agrawal Jayendra Kumar Avanish Kumar Anumeha Arvind R. Yadav Department of Electronics and Communication National Institute of Technology Jamshedpur Jamshedpur India Department of Electrical Engineering Delhi Technological University Delhi India Department of Electronics and Communication Government Women?s Polytechnic Jamshedpur Jamshedpur India Department of Electronics and Instrumentation Engineering Institute of Technology Nirma University Ahmedabad India

ISBN: (数字)9798331505745

ISBN: (纸本)9798331505752

The Internet of Things (IoT) has revolutionized global device interconnectivity, fostering seamless data exchange through expansive sensing networks. Similarly, swarm robotics emulates the collective behaviors observed in nature, such as bird flocks and ant colonies, aiming to adapt these principles for practical use. This paper explores the dynamics of robotic swarms operating under a centralized network model using master-slave communication. Two implementation approaches are examined: direct, small-scale interactions utilizing device MAC addresses and large-scale connectivity facilitated by an IoT-based cloud server. Our experiments employ the NodeMCU ESP8266 platform, which utilizes the IEEE 802.11 Wi-Fi standard for data handling and transfer. For cloud-based communication, we utilize the ThingSpeak server to manage data flow. This study evaluates the strengths and limitations of these approaches in fostering swarm behavior, aiming to derive strategies for enhancing the performance and coordination of swarm robotic systems.

关键词： Cloud computing Robot kinematics swarm robotics Robot sensing systems Main-secondary Topology Internet of Things Servers Wireless fidelity Standards

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