The DOI matches its Crossref record; 21 of the 22 references it cites were found in a registry or an index.
Programmable self-assembly in a thousand-robot swarm
Abstract
Large-scale robotic self-assembly: When individuals swarm, they must somehow communicate to direct collective motion. Swarms of robots need to deal with outliers, such as robots that move more slowly than the rest. Rubenstein et al. created a large swarm of programmed robots that can form collaborations using only local information. The robots could communicate only with nearby members, within about three times their diameter. They were able to assemble into complex preprogrammed shapes. If the robots' formation hit snags when they bumped into one another or because of an outlier, additional algorithms guided them to rectify their collective movements. Science , this issue p. 795
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BackgroundMethodServing by local consensus in the public service location game
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“, ants and bees) and biological multi-cellular systems [33–35] and swarms of robots [12, 36].”
BackgroundDesign of Swarm Robots Formation Control System Based on Vision Guidance
Lan, R., Wang, X., Xiao, Z., et al. (2019) · IEEE/ASME International Conference on Advanced Intelligent Mechatronics · doi:10.1109/aim.2019.8868886 · Cited by 3
“used 1024 kilobot robots to form any shape by acquiring information through infrared communication between robots, in which one robot gets its global position by the calculation of others’ position [3].”
MethodGroup Behavior on Emergency Mode Transferring in Autonomous Multi-Robot Systems with Subgroups
Nogami, T., & Wang, Z. (2019) · IEEE International Conference on Robotics and Biomimetics (ROBIO) · doi:10.1109/robio49542.2019.8961571 · Cited by 3
Moustafa, N., Iglesias, A., & Gálvez, A. (2019) · International Conference on Software, Knowledge, Information Management and Applications (SKIMA) · doi:10.1109/skima47702.2019.8982462 · Cited by 3
“Recently, a swarm of one thousand kilobots has been reported in the literature [22].”
BackgroundZhang, Y., & Balkcom, D. (2020) · Springer proceedings in advanced robotics · doi:10.1007/978-3-030-44051-0_41 · Cited by 3
“[12], along with algorithms for planning mechanisms allowing kilobots to form 2D shapes.”
MethodA Parallel Evolutionary Algorithm with Value Decomposition for Multi-agent Problems
Li, G., Duan, Q., & Shi, Y. (2020) · Lecture notes in computer science · doi:10.1007/978-3-030-53956-6_57 · Cited by 3
A Fast, Accurate, and Scalable Probabilistic Sample-Based Approach for Counting Swarm Size
Wang, H., & Rubenstein, M. (2020) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/icra40945.2020.9196529 · Cited by 3
“In [1] the shape is sized to fit the number of robots in the swarm.”
BackgroundMethodSelf-citationWang, Q., Huang, J., & Mao, X. (2020) · International Conference on Automation, Control and Robotics Engineering (CACRE) · doi:10.1109/cacre50138.2020.9230325 · Cited by 3
Reinforcement learning reveals fundamental limits on the mixing of active particles
Schildknecht, D., Popova, A. N., Stellwagen, J., & Thomson, M. W. (2021) · Soft Matter · doi:10.1039/d1sm01400e · Cited by 3
Errors in Collective Robotic Construction
Chen, J., Liu, Y., Pacheck, A., et al. (2022) · Springer proceedings in advanced robotics · doi:10.1007/978-3-030-92790-5_21 · Cited by 3
Fabrication of Artificial Muscle from Microtubules, Kinesins, and DNA Origami Nanostructures
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Ye, F., Abdulali, A., & Fumiya Iida, A. (2022) · Frontiers in Robotics and AI · doi:10.3389/frobt.2022.980586 · Cited by 2
“These researches take the interactions between individuals as a method of communication (Rubenstein et al., 2014; Sharma et al., 2020).”
BackgroundDevelopment of mobile robot network based on data sharing in the Ethereum platform
Shibata, Y., & Morioka, K. (2023) · IEEE/SICE International Symposium on System Integration (SII) · doi:10.1109/sii55687.2023.10039100 · Cited by 3
“In recent years, there have been demonstrations with actual robots on the scale of 1,000 units [5].”
BackgroundTanveer, M. H., Sgorbissa, A., & Thomas, A. (2019) · Lecture notes in electrical engineering · doi:10.1007/978-3-030-31993-9_21 · Cited by 3
Gaudl, S. E. (2016) · The University of Bath Online Publications Store (The University of Bath) · Cited by 4
An Algorithmic Framework for Shape Formation Problems in Self-Organizing Particle SystemsPreprint
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“autonomous robots that have limited sensing, and communication ranges, and that can freely move in a given area. They follow a variety of goals, including for example shape formation problems (e.g., [9, 14]). Surveys of recent results in swarm robotics can be found in [11, 12]. While the analytical techniques develope…”
BackgroundOptimal Estimation and Control of Large Collaborative Swarms using Random Finite Set Theory
Doerr, B. G. (2019) · University of Minnesota Digital Conservancy (University of Minnesota) · Cited by 3
Cyber Physical System for Enhancement in Security While Using Cyber
Bhatia, A., Kumar, A., & Sood, D. (2024) · Advances in human and social aspects of technology book series · doi:10.4018/979-8-3693-9235-5.ch005 · Cited by 2
Untethered Autonomous Holonomic Mobile Micromanipulator for Operations in Isolated Confined Spaces
Kinoshita, R., Minegishi, R., Sekine, C., et al. (2025) · Advanced Intelligent Systems · doi:10.1002/aisy.202400872 · Cited by 2
Towards Self-Assembling 3D-Printed Shapes Through Βiomimetic Μechanical Interlocking
Marte, T., Koltsakidis, S., Profitiliotis, T., et al. (2025) · Biomimetics · doi:10.3390/biomimetics10060400 · Cited by 2
“In addition, approaches involving robotics and active materials have broadened the scope of related research, even if these systems fall outside the strict definitions of self-assembly [10].”
Decentralised construction of a global coordinate system in a large swarm of minimalistic robots
Pluháček, M., Garnier, S., & Reina, A. (2025) · Swarm Intelligence · doi:10.1007/s11721-025-00251-4 · Cited by 2
Trajectory Generation for Quadrotors Air Parallel Docking With Time-Varying Avoidance Constraints
Zhang, J., Li, F., Xin, Y., et al. (2025) · IEEE Robotics and Automation Letters · doi:10.1109/lra.2025.3625489 · Cited by 2
“Studies [7], [8], [9] interconnect submodules to create a 3D shape.”
Hu, B.-B., Yao, W., Zhou, Y., Wei, H., & Lv, C. (2025) · IEEE Transactions on Robotics · doi:10.1109/tro.2025.3626654 · Cited by 2
“…of potential infeasibility and low efficiency in goal-assignment approaches [13]–[20] and unclear path-crossing-minimal mechanisms in goal-assignment-free approaches [12], [21]– [28], the challenging problem of MPCM navigation in obstacle environments still requires further investigation.”
Influential
Metadata
- Authors
- Rubenstein, M., Cornejo, A., & Nagpal, R.
- Affiliations
- Harvard University (US)
- Corresponding author
- Rubenstein, Michael
- Venue
- Science
- Published
- 2014-08-15
- Volume
- 345
- Issue
- 6198
- Pages
- 795-799
- ISSN
- 0036-8075 (ISSN-L)
- 1095-9203
- OpenAlex
- W2030775133
- Semantic Scholar
- c5ab840850ab57f2f14b67a5485fa3fd727b33b8
- Cited by
- 1,308
- References
- 22
- Citations by year
- 2026: 115 · 2025: 129 · 2024: 110 · 2023: 122 · 2022: 118 · 2021: 112 · 2020: 105 · 2019: 135 · 2018: 117 · 2017: 94 · 2016: 73 · 2015: 66 · 2014: 11
- FWCI
- 98.67
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Science (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Physical Sciences › Engineering › Mechanical Engineering › Modular Robots and Swarm Intelligence
- Physical Sciences › Engineering › Control and Systems Engineering › Distributed Control Multi-Agent Systems
- Physical Sciences › Physics and Astronomy › Condensed Matter Physics › Micro and Nano Robotics
- Keywords
- programmable self-assembly, swarm robotics, shape formation, decentralized systems, autonomous robots, local interactions, artificial swarms, two-dimensional shapes
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