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In swarm robotics, collective transport refers to the cooperative movement of a large object by multiple small robots, each with limited individual capabilities such as sensing, mobility, and communication. When working together, however, these simple agents can achieve complex tasks. This study explores a collective transport method based on the caging approach, which involves surrounding the object in a way that restricts its movement while still allowing limited motion, effectively preventing escape from the robot formation. The proposed approach is structured into four main phases: locating the object, recruiting additional robots, forming an initial cage around the object, and finally, performing the transportation. The method is tested using simulations in the CoppeliaSim environment, employing a team of Khepera-III robots. Performance metrics include execution time for the search and recruitment phases, and both execution time and trajectory accuracy, via a normalized error, for the transport phase. To further validate the method, a comparison is made between the caging-based strategy and a traditional pushing strategy.
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http://dx.doi.org/10.3390/s25165063 | DOI Listing |
Proc Natl Acad Sci U S A
September 2025
Department of Artificial Intelligence, Donders Center for Cognition, Radboud University, Nijmegen, GD 6525, Netherlands.
We present a geometric design rule for size-controlled clustering of self-propelled particles. We show that active particles that tend to rotate under an external force have an intrinsic, signed parameter with units of curvature which we call curvity, that can be derived from first principles. Experiments with robots and numerical simulations show that properties of individual robots (radius and curvity) control pair cohesion in a binary system, and the stability of flocking and self-limiting clustering in a swarm, with applications in metamaterials and in embodied decentralized control.
View Article and Find Full Text PDFFood Sci Biotechnol
October 2025
Department of Life Sciences, Somaiya Vidyavihar University, Vidyavihar, Mumbai, India.
Challenges such as a downward trend in cultivation and post-harvest losses lead to increased gap in cocoa bean supply and demand. This review deals with the recent AI models used in farming, processing, and supply chain of cocoa beans. Farming models viz.
View Article and Find Full Text PDFProc Natl Acad Sci U S A
September 2025
Department of Chemical Engineering, University of Michigan, Ann Arbor, MI 48109.
In recent years the functionality of synthetic active microparticles has edged even closer to that of their biological counterparts. However, we still lack the understanding needed to recreate at the microscale key features of autonomous behavior exhibited by microorganisms or swarms of macroscopic robots. In this study, we propose a model for a three-dimensional deformable cellular composite particle consisting of self-propelled rod-shaped colloids confined within a flexible vesicle-representing a superstructure we call a "flexicle" that couples particle deformation to the internal dynamics of the internal active components.
View Article and Find Full Text PDFNat Commun
September 2025
Department of Artificial Intelligence, Donders Center for Cognition, Radboud University, Nijmegen, The Netherlands.
Cooperative transport is a striking phenomenon where multiple agents join forces to transit a payload too heavy for the individual. While social animals such as ants are routinely observed to coordinate transport at scale, reproducing the effect in artificial swarms remains challenging, as it requires synchronization in a noisy many-body system. Here we show that cooperative transport spontaneously emerges in swarms of stochastic self-propelled robots.
View Article and Find Full Text PDFSensors (Basel)
August 2025
Department of Systems Engineering and Computation, State University of Rio de Janeiro, Rua são Francisco Xavier 524, Rio de Janeiro 20000-000, Brazil.
In swarm robotics, collective transport refers to the cooperative movement of a large object by multiple small robots, each with limited individual capabilities such as sensing, mobility, and communication. When working together, however, these simple agents can achieve complex tasks. This study explores a collective transport method based on the caging approach, which involves surrounding the object in a way that restricts its movement while still allowing limited motion, effectively preventing escape from the robot formation.
View Article and Find Full Text PDF