Optimized user-guided motion control of modular robots

Anastasia Bolotnikova, Kevin Holdcroft, Henry Cerbone, Christoph Belke, Auke Ijspeert and Jamie Paik ()
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Anastasia Bolotnikova: Ecole Polytechnique Fédérale de Lausanne (EPFL)
Kevin Holdcroft: Ecole Polytechnique Fédérale de Lausanne (EPFL)
Henry Cerbone: Ecole Polytechnique Fédérale de Lausanne (EPFL)
Christoph Belke: Ecole Polytechnique Fédérale de Lausanne (EPFL)
Auke Ijspeert: Ecole Polytechnique Fédérale de Lausanne (EPFL)
Jamie Paik: Ecole Polytechnique Fédérale de Lausanne (EPFL)

Nature Communications, 2025, vol. 16, issue 1, 1-12

Abstract: Abstract Transferring motion instructions from a user enables robots to perform new and unforeseen operations. Robot collectives, in particular, offer greater adaptability to changing tasks and environments. However, effectively transferring motion instructions becomes challenging as the collective’s shape and size evolve. These changes often require additional system constraints to maintain robust motion control, which typically depends on pre-programmed knowledge of new tasks, ultimately limiting the collective’s adaptability. To overcome the above challenges, we propose a physical and computational platform for user-guided control of self-reconfigurable modular robots. This platform consists of an optimization scheme for online processing of user commands, which prevents any modular robot actions that would violate system or environment constraints. The second component consists of Joint-space Joysticks, which match the robot’s morphology, enabling the user to control diverse and dynamically changing modular robot structures through direct physical interaction. We present a platform that enables users to safely control modular, shape-changing robots through a physical interface. We demonstrate the platform’s efficacy and generalizability across a diverse set of modular robot morphologies using two independent robotic systems — Mori3 and Roombots — performing a range of tasks including pick-and-place, human assistance, legged locomotion, and workspace expansion.

Date: 2025
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DOI: 10.1038/s41467-025-63706-6

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