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This article details DNPush, a novel control algorithm enabling multi-robot cooperative transport without inter-robot communication or explicit object modeling. By leveraging local force measurements and a reciprocal-sine law, the system achieves precise velocity convergence and rotational equilibrium in both simulation and hardware experiments with soft tactile robots. The work advances distributed machine learning and control theory for robotic swarms operating under strict communication constraints.
DNPush: Distributed Nonparallel Pushing Force Control of Multi-Robot Systems for Object Transportation
arXiv:2610.04764v1 Announce Type: new Abstract: This letter proposes DNPush, a Distributed Nonparallel Pushing force controller for cooperative object transport without inter-robot communication. Each robot uses local force measurements, a preassigned force weight, and a locally expressed desired transport direction, without requiring an object model, contact locations, a CoM estimate, or moment arm magnitudes online. DNPush regulates nonparallel force magnitudes from local force direction misalignments through a reciprocal-sine law. Under the stated contact conditions, Lyapunov analysis with LaSalle's invariance principle proves convergence to a unique rotational equilibrium, where perpendicular force contributions cancel and the net torque from normal forces is zero. Object velocity converges to the desired transport direction, and suitable contact regions exist for convex polygons. Simulations isolate the reciprocal-sine scaling mechanism, five-robot coordination, and active rotational damping. Hardware experiments with soft tactile differential-drive robots achieve a velocity direction error of 0.61 deg +/- 0.79 deg over five trials with a fixed transport direction and demonstrate object transport through waypoints with three robots.
Abstract:This letter proposes DNPush, a Distributed Nonparallel Pushing force controller for cooperative object transport without inter-robot communication. Each robot uses local force measurements, a preassigned force weight, and a locally expressed desired transport direction, without requiring an object model, contact locations, a CoM estimate, or moment arm magnitudes online. DNPush regulates nonparallel force magnitudes from local force direction misalignments through a reciprocal-sine law. Under the stated contact conditions, Lyapunov analysis with LaSalle's invariance principle proves convergence to a unique rotational equilibrium, where perpendicular force contributions cancel and the net torque from normal forces is zero. Object velocity converges to the desired transport direction, and suitable contact regions exist for convex polygons. Simulations isolate the reciprocal-sine scaling mechanism, five-robot coordination, and active rotational damping. Hardware experiments with soft tactile differential-drive robots achieve a velocity direction error of 0.61 deg +/- 0.79 deg over five trials with a fixed transport direction and demonstrate object transport through waypoints with three robots.
8 pages, 8 figures. Submitted to IEEE Robotics and Automation Letters
Robotics (cs.RO); Systems and Control (eess.SY)
arXiv:2610.04764 [cs.RO]
(or arXiv:2610.04764v1 [cs.RO] for this version)
https://doi.org/10.48550/arXiv.2610.04764 Focus to learn more arXiv-issued DOI via DataCite (pending registration)
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