Modular Robotics

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Modular robotics studies how robots made from interchangeable parts can change shape, share capabilities, or assemble into systems suited to different tasks. Approaches include mechanical docking and self-assembly, optimization and motion planning, decentralized or graph-based control, and learning methods that transfer across configurations. Researchers apply these ideas to manipulation, locomotion, aerial and underwater robots, construction, field operations, and human-robot interaction. A central challenge is making reconfiguration reliable at scale while ensuring that modules remain mechanically, computationally, and behaviorally compatible after they are combined.

Latest papers

46 papers7 papers in the last four weeks, level with the four weeks before. 0.0% of all new papers.

May 6, 2026

3D Printing of Passively Actuated Self-Folding Robots with Integrated Functional Modules

We introduce an elastic-driven self-folding approach that fabricates robots directly from flat 3D-printed conductive PLA nets. Elastic bands routed through printed hooks store energy that folds the sheet into programmed 3D geometries, while the flat state allows accurate placement of electronics and magnets before deployment. The same substrate doubles as electrodes for capacitive touch and supports a reusable platform I/O palette with Hall sensors and eccentric rotating mass (ERM) motors for docking detection and vibration actuation. We also derive a closed-form folding model that balances hinge stiffness with elastic band moment to predict equilibrium fold angles; experiments validate the model and yield a design map linking hinge thickness, band size, and hook spacing to target angles. Using this workflow we realize multiple polyhedral modules and demonstrate three applications: a cube that highlights the potential of self-folding for scalable modular robot collectives, a deployable gripper, and a tendon-driven finger. The method is low cost, stimulus-free, and integrates actuation and sensing.

Gaolin Ge, Qifeng Yang, Haoran Lu +3

Mechanical Engineering, University of Washington, Seattle, WA, USA. · Electrical & Computer Engineering, University of Washington, Seattle, WA, USA. · Computer Science and Engineering, University of Notre Dame, Notre Dame, IN, USA. +1

Modular Robotics Robotics Soft Robotics

Apr 8, 2026

AEROS: A Single-Agent Operating Architecture with Embodied Capability Modules

Robotic systems lack a principled abstraction for organizing intelligence, capabilities, and execution in a unified manner. Existing approaches either couple skills within monolithic architectures or decompose functionality into loosely coordinated modules or multiple agents, often without a coherent model of identity and control authority. We argue that a robot should be modeled as a single persistent intelligent subject whose capabilities are extended through installable packages. We formalize this view as AEROS (Agent Execution Runtime Operating System), in which each robot corresponds to one persistent agent and capabilities are provided through Embodied Capability Modules (ECMs). Each ECM encapsulates executable skills, models, and tools, while execution constraints and safety guarantees are enforced by a policy-separated runtime. This separation enables modular extensibility, composable capability execution, and consistent system-level safety. We evaluate a reference implementation in PyBullet simulation with a Franka Panda 7-DOF manipulator across eight experiments covering re-planning, failure recovery, policy enforcement, baseline comparison, cross-task generality, ECM hot-swapping, ablation, and failure boundary analysis. Over 100 randomized trials per condition, AEROS achieves 100% task success across three tasks versus baselines (BehaviorTree.CPP-style and ProgPrompt-style at 92--93%, flat pipeline at 67--73%), the policy layer blocks all invalid actions with zero false acceptances, runtime benefits generalize across tasks without task-specific tuning, and ECMs load at runtime with 100% post-swap success.

Xue Qin, Simin Luan, John See +2

School of Software, Harbin Institute of Technology, Harbin, China · School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China · School of Mathematical and Computer Sciences, Heriot-Watt University, Malaysia Campus, Putrajaya, 62200, Malaysia +1

Modular Robotics

Apr 7, 2026

MARS-Dragonfly: Agile and Robust Flight Control of Modular Aerial Robot Systems

Modular Aerial Robot Systems (MARS) comprise multiple drone units with reconfigurable connected formations, providing high adaptability to diverse mission scenarios, fault conditions, and payload capacities. However, existing control algorithms for MARS rely on simplified quasi-static models and rule-based allocation, which generate discontinuous and unbounded motor commands. This leads to attitude error accumulation as the number of drone units scales, ultimately causing severe oscillations during docking, separation, and waypoint tracking. To address these limitations, we first design a compact mechanical system that enables passive docking, detection-free passive locking, and magnetic-assisted separation using a single micro servo. Second, we introduce a force-torque-equivalent and polytope-constraint virtual quadrotor that explicitly models feasible wrench sets. Together, these abstractions capture the full MARS dynamics and enable existing quadrotor controllers to be applied across different configurations. We further optimize the yaw angle that maximizes control authority to enhance agility. Third, building on this abstraction, we design a two-stage predictive-allocation pipeline: a constrained predictive tracker computes virtual inputs while respecting force/torque bounds, and a dynamic allocator maps these inputs to individual modules with balanced objectives to produce smooth, trackable motor commands. Simulations across over 10 configurations and real-world experiments demonstrate stable docking, locking, and separation, as well as effective control performance. To our knowledge, this is the first real-world demonstration of MARS achieving agile flight and transport with 40 deg peak pitch while maintaining an average position error of 0.0896 m. The video is available at: https://youtu.be/yqjccrIpz5o

Rui Huang, Zhiqian Cai, Siyu Tang +6

Department of Electrical and Computer Engineering, National University of Singapore, Singapore 117583, Singapore · Engineering Design and Innovation Centre, National University of Singapore, Singapore 117583, Singapore

Aerial Robotics Modular Robotics Quadrotor Control

Apr 6, 2026

ZipFold: Modular Actuators for Scaleable Adaptive Robots

There is a growing need for robots that can change their shape, size and mechanical properties to adapt to evolving tasks and environments. However, current shape-changing systems generally utilize bespoke, system-specific mechanisms that can be difficult to scale, reconfigure or translate from one application to another. This paper introduces a compact, easy-to-fabricate deployable actuator that achieves reversible scale and stiffness transformations through compound folding and zipping of flexible 3D-printed plastic strips into square-section deployable beams. The simple actuation method allows for smooth, continuous transitions between compact (flexible) and expanded (quasi-rigid) states, facilitating diverse shape and stiffness transformations when modules are combined into larger assemblies. The actuator's mechanical performance is characterized and an integrated system involving a four-module adaptive walking robot is demonstrated.

Niklas Hagemann, Daniela Rus

Computer Science and Artificial Intelligence Laboratory, MIT, Cambridge, MA 02139 USA

Modular Robotics

Apr 4, 2026

COMB: Common Open Modular robotic platform for Bees

Experimental access to real honeybee colonies requires robotic systems capable of operating within limited spatial constraints, tolerating hive-specific fouling and environmental conditions, and supporting both sensing and localized actuation without frequent hardware redesign. This paper introduces COMB, a compact, open-source, modular mechatronic platform designed for in-hive experiments within standard observation-hive frames. The platform integrates a XY positioning stage, a Movable Access Window (MAW) for sealed tool access through the hive boundary, interchangeable payload modules, and an embedded control architecture that enables repeatable trajectory execution and signal generation. The platform's capabilities are demonstrated through three representative modules: a biomimetic dance-and-signaling payload, a close-range comb scanner, and an electromagnetic wing actuator for localized oscillatory stimulation. This paper details the hardware and software design of COMB, outlines its operational capabilities, and describes the supporting infrastructure for conducting real-world in-hive experiments. The platform is characterized in engineering terms through tracking waggle-trajectory executions, performing multi-image stitching for repeated comb mosaics, and conducting video-based spectral analysis of the wing actuator. These results position COMB as a reusable experimental robotics platform for controlled in-hive sensing and actuation, and as a compact, generalized successor to earlier task-specific honeybee robotic systems.

Pranav Kedia, Marie Messerich, Tim Landgraf

Department of Computer and Information Science, University of Konstanz, Germany · Centre for the Advanced Study of Collective Behaviour, University of Konstanz, Konstanz, Germany · Dahlem Center for Machine Learning and Robotics, Freie Universität Berlin, Berlin, Germany

Robotics Modular Robotics Robotic Data Collection Robotic Inspection

Mar 31, 2026

Reconfiguration of supernumerary robotic limbs for human augmentation

Wearable robots aim to seamlessly adapt to humans and their environment with personalized interactions. Existing supernumerary robotic limbs (SRLs), which enhance the physical capabilities of humans with additional extremities, have thus far been developed primarily for task-specific applications in structured industrial settings, limiting their adaptability to dynamic and unstructured environments. Here, we introduce a novel reconfigurable SRL framework grounded in a quantitative analysis of human augmentation to guide the development of more adaptable SRLs for diverse scenarios. This framework captures how SRL configuration shapes workspace extension and human-robot collaboration. We define human augmentation ratios to evaluate collaborative, visible extended, and non-visible extended workspaces, enabling systematic selection of SRL placement, morphology, and autonomy for a given task. Using these metrics, we demonstrate how quantitative augmentation analysis can guide the reconfiguration and control of SRLs to better match task requirements. We validate the proposed approach through experiments with a reconfigurable SRL composed of origami-inspired modular elements. Our results suggest that reconfigurable SRLs, informed by quantitative human augmentation analysis, offer a new perspective for providing adaptable human augmentation and assistance in everyday environments.

Mustafa Mete, Anastasia Bolotnikova, Alexander Schuessler +1

Reconfigurable Robotics Lab, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland. · Laboratory for Analysis and Architecture of Systems (LAAS), CNRS, Toulouse, France.

Robotics Assistive Robotics Human-Robot Collaboration Modular Robotics

Mar 29, 2026

Transferability Through Cooperative Competitions

This paper presents a novel framework for cooperative robotics competitions (coopetitions) that promote the transferability and composability of robotics modules, including software, hardware, and data, across heterogeneous robotic systems. The framework is designed to incentivize collaboration between teams through structured task design, shared infrastructure, and a royalty-based scoring system. As a case study, the paper details the implementation and outcomes of the first euROBIN Coopetition, held under the European Robotics and AI Network (euROBIN), which featured fifteen robotic platforms competing across Industrial, Service, and Outdoor domains. The study highlights the practical challenges of achieving module reuse in real-world scenarios, particularly in terms of integration complexity and system compatibility. It also examines participant performance, integration behavior, and team feedback to assess the effectiveness of the framework. The paper concludes with lessons learned and recommendations for future coopetitions, including improveme

Rodrigo Serra, Carlos Azevedo, André Silva +6

Institute for Systems and Robotics / LARSyS, Instituto Superior Técnico, University of Lisbon · Laboratory for Automatics and Systems, Instituto Pedro Nunes · INRIA, CNRS, Université de Lorraine, Nancy, France +3

Robotics Modular Robotics Multi-Robot Systems

Mar 19, 2026

Introducing M: A Modular, Modifiable Social Robot

We present M, an open-source, low-cost social robot platform designed to reduce platform friction that slows social robotics research by making robots easier to reproduce, modify, and deploy in real-world settings. M combines a modular mechanical design, multimodal sensing, and expressive yet mechanically simple actuation architecture with a ROS2-native software package that cleanly separates perception, expression control, and data management. The platform includes a simulation environment with interface equivalence to hardware to support rapid sim-to-real transfer of interaction behaviors. We demonstrate extensibility through additional sensing/actuation modules and provide example interaction templates for storytelling and two-way conversational coaching. Finally, we report real-world use in participatory design and week-long in-home deployments, showing how M can serve as a practical foundation for longitudinal, reproducible social robotics research.

Victor Nikhil Antony, Zhili Gong, Yoonjae Kim +1

Department of Computer Science, Johns Hopkins University, USA · Department of Mechanical Engineering, Rice University, USA

Social Robotics Modular Robotics Human-Robot Interaction

Mar 6, 2026

Robodimm: A Physics-Grounded Framework for Automated Actuator Sizing in Scalable Modular Robots

Selecting an appropriate motor-gearbox combination is a critical design task in robotics because it directly affects cost, mass, and dynamic performance. This process is especially challenging in modular robots with closed kinematic chains, where joint torques are coupled and actuator inertia propagates through the mechanism. We present Robodimm, a software framework for automated actuator sizing in scalable robot architectures. By leveraging Pinocchio for dynamics and Pink for inverse kinematics, Robodimm uses a Karush-Kuhn-Tucker (KKT) formulation for constrained inverse dynamics. The platform supports parametric scaling, interactive trajectory programming through jog modes, and a two-round validation workflow that addresses actuator self-weight effects.

J. L. Torres, M. Munoz, J. D. Alvarez +2

CIESOL-ceiA3, Department of Engineering, University of Almería, Spain · CIESOL-ceiA3, Department of Computer Science, University of Almería, Spain

Modular Robotics Mechanism Design

Mar 5, 2026

Designing and Validating a Self-Aligning Tool Changer for Modular Reconfigurable Manipulation Robots

Modular reconfigurable robots require reliable mechanisms for automated module exchange, but conventional rigid active couplings often fail due to inevitable positioning and orientational errors. To address this, we propose a misalignment-tolerant tool-changing system. The hardware features a motor-driven coupling utilizing passive self-alignment geometries, specifically chamfered receptacles and triangular lead-in guides, to robustly compensate for angular and lateral misalignments without complex force sensors. To make this autonomous exchange practically feasible, the mechanism is complemented by a compact rotating tool exchange station for efficient module storage. Real-world autonomous tool-picking experiments validate that the self-aligning features successfully absorb execution errors, enabling highly reliable robotic tool reconfiguration.

Mahfudz Maskur, Takuya Kiyokawa, Kensuke Harada

Department of Systems Innovation, Graduate School of Engineering Science, The University of Osaka, 1-3 Machikaneyama, Toyonaka, Osaka, Japan. · Industrial Cyber-physical Systems Research Center, The National Institute of Advanced Industrial Science and Technology (AIST), 2-3-26 Aomi, Koto-ku, Tokyo, Japan.

Modular Robotics Robotic Manipulation Robotic Insertion

Mar 5, 2026

Gait Generation Balancing Joint Load and Mobility for Legged Modular Robots with Easily Detachable Joints

While modular robots offer versatility, excessive joint torque during locomotion poses a significant risk of mechanical failure, especially for detachable joints. To address this, we propose an optimization framework using the NSGA-III algorithm. Unlike conventional approaches that prioritize mobility alone, our method derives Pareto optimal solutions to minimize joint load while maintaining necessary locomotion speed and stability. Simulations and physical experiments demonstrate that our approach successfully generates gait motions for diverse environments, such as slopes and steps, ensuring structural integrity without compromising overall mobility.

Kennosuke Chihara, Takuya Kiyokawa, Kensuke Harada

Department of Systems Innovation, Graduate School of Engineering Science, The University of Osaka, 1-3 Machikaneyama, Toyonaka, Osaka, Japan. · Industrial Cyber-physical Systems Research Center, The National Institute of Advanced Industrial Science and Technology (AIST), 2-3-26 Aomi, Koto-ku, Tokyo, Japan.

Legged Robotics Robot Motion Generation Modular Robotics

Mar 2, 2026

A Novel Modular Cable-Driven Soft Robotic Arm with Multi-Segment Reconfigurability

This paper presents a novel, modular, cable-driven soft robotic arm featuring multi-segment reconfigurability. The proposed architecture enables a stackable system with independent segment control, allowing scalable adaptation to diverse structural and application requirements. The system is fabricated from soft silicone material and incorporates embedded tendon-routing channels with a protective dual-helical tendon structure. Experimental results showed that modular stacking substantially expanded the reachable workspace: relative to the single-segment arm, the three-segment configuration achieved up to a 13-fold increase in planar workspace area and a 38.9-fold increase in workspace volume. Furthermore, this study investigated the effect of silicone stiffness on actuator performance. The results revealed a clear trade-off between compliance and stiffness: softer silicone improved bending flexibility, while stiffer silicone improved structural rigidity and load-bearing stability. These results highlight the potential of stiffness tuning to balance compliance and strength for configuring scalable, reconfigurable soft robotic arms.

Moeen Ul Islam, Cheng Ouyang, Xinda Qi +3

Department of Agricultural and Biological Engineering, Mississippi State University, MS, USA · Department of Electrical and Computer Engineering, Michigan State University, MI, USA · Texas A&M AgriLife Research and Extension Center in Dallas, Texas A&M University, TX, USA

Soft Robotics Modular Robotics Tendon-Driven Actuation

Feb 23, 2026

Scalable Low-Density Distributed Manipulation Using an Interconnected Actuator Array

Distributed Manipulator Systems, composed of arrays of robotic actuators necessitate dense actuator arrays to effectively manipulate small objects. This paper presents a system composed of modular 3-DoF robotic tiles interconnected by a compliant surface layer, forming a continuous, controllable manipulation surface. The compliant layer permits increased actuator spacing without compromising object manipulation capabilities, significantly reducing actuator density while maintaining robust control, even for smaller objects. We characterize the coupled workspace of the array and develop a manipulation strategy capable of translating objects to arbitrary positions within an N X N array. The approach is validated experimentally using a minimal 2 X 2 prototype, demonstrating the successful manipulation of objects with varied shapes and sizes.

Bailey Dacre, Rodrigo Moreno, Jørn Lambertsen +2

Robotic Manipulation Modular Robotics

Feb 23, 2026

Positioning Modular Co-Design in Future HRI Design Research

Design-oriented HRI is increasingly interested in robots as long-term companions, yet many designs still assume a fixed form and a stable set of functions. We present an ongoing design research program that treats modularity as a designerly medium - a way to make long-term human-robot relationships discussable and material through co-design. Across a series of lifespan-oriented co-design activities, participants repeatedly reconfigured the same robot for different life stages, using modular parts to express changing needs, values, and roles. From these outcomes, we articulate PAS (Personalization-Adaptability-Sustainability) as a human-centered lens on how people enact modularity in practice: configuring for self-expression, adapting across transitions, and sustaining robots through repair, reuse, and continuity. We then sketch next steps toward a fabrication-aware, community-extensible modular platform and propose evaluation criteria for designerly HRI work that prioritize expressive adequacy, lifespan plausibility, repairability-in-use, and responsible stewardship - not only usability or performance.

Lingyun Chen, Qing Xiao, Zitao Zhang +2

Luddy School of Informatics, Computing, and Engineering, Indiana University Bloomington, Bloomington, IN, USA · Human-Computer Interaction Institute, Carnegie Mellon University, Pittsburgh, PA, USA

Human-Robot Interaction Robotics Modular Robotics

Feb 22, 2026

Design and Control of Modular Magnetic Millirobots for Multimodal Locomotion and Shape Reconfiguration

Modular small-scale robots offer the potential for on-demand assembly and disassembly, enabling task-specific adaptation in dynamic and constrained environments. However, existing modular magnetic platforms often depend on workspace collisions for reconfiguration, employ bulky three-dimensional electromagnetic systems, and lack robust single-module control, which limits their applicability in biomedical settings. In this work, we present a modular magnetic millirobotic platform comprising three cube-shaped modules with embedded permanent magnets, each designed for a distinct functional role: a free module that supports self-assembly and reconfiguration, a fixed module that enables flip-and-walk locomotion, and a gripper module for cargo manipulation. Locomotion and reconfiguration are actuated by programmable combinations of time-varying two-dimensional uniform and gradient magnetic field inputs. Experiments demonstrate closed-loop navigation using real-time vision feedback and A* path planning, establishing robust single-module control capabilities. Beyond locomotion, the system achieves self-assembly, multimodal transformations, and disassembly at low field strengths. Chain-to-gripper transformations succeeded in 90% of trials, while chain-to-square transformations were less consistent, underscoring the role of module geometry in reconfiguration reliability. These results establish a versatile modular robotic platform capable of multimodal behavior and robust control, suggesting a promising pathway toward scalable and adaptive task execution in confined environments.

Erik Garcia Oyono, Jialin Lin, Dandan Zhang

Department of Bioengineering, Imperial College London, London, United Kingdom.

Modular Robotics Robotics Robot Locomotion

Feb 20, 2026

Downwash-aware Configuration Optimization for Modular Aerial Systems

This work proposes a framework that generates and optimally selects task-specific assembly configurations for a large group of homogeneous modular aerial systems, explicitly enforcing bounds on inter-module downwash. Prior work largely focuses on planar layouts and often ignores aerodynamic interference. In contrast, firstly we enumerate non-isomorphic connection topologies at scale; secondly, we solve a nonlinear program to check feasibility and select the configuration that minimizes control input subject to actuation limits and downwash constraints. We evaluate the framework in physics-based simulation and demonstrate it in real-world experiments.

Mengguang Li, Heinz Koeppl

Department of Electrical Engineering and Information Technology, Technische Universität Darmstadt, 64287 Darmstadt, Germany.

Aerial Robotics Modular Robotics