Chicaiza Claudio, Fernando
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Chicaiza Claudio, Fernando
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Ambato

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Dual-Arm Mobile Manipulator Teleoperation With Coupled Rate-Position Mapping Under Time-Varying Delays

2025 , Chicaiza Claudio, Fernando , Emanuel Slawiñski , Vicente Mut

Bilateral teleoperation of dual-arm mobile manipulators presents considerable challenges. These include increased kinematic redundancy, coordination complexity, and sensitivity to time-varying communication delays. Most existing approaches control each arm independently using leader position-based mappings; however, the teleoperation of mobile dual-arm systems mechanically coupled through an articulated torso remains largely unexplored. Unlike previous studies that primarily emphasize controller tuning, this work emphasizes the critical role of command mapping design in achieving effective teleoperation. Specifically, it analyzes a coupled rate/nonlinear-position mapping strategy that enables coordinated motion in a torso-equipped dual-arm mobile manipulator operated through a dual-leader haptic interface. The proposed framework extends existing single-arm teleoperation schemes by introducing a coupled reference generation mechanism, where the reference for the secondary arm depends on both the position of the secondary leader and the rate-position-type reference of the primary arm. A two-stage stability analysis, based on the Lyapunov-Krasovskii criterion and numerical simulations, is conducted to determine the parameter conditions required to ensure bounded coordination errors in the presence of time-varying communication delays. Preliminary human-in-the-loop tests in dual-arm pick-and-place tasks support the theoretical findings and demonstrate a clear dependence of motion stability on the structure of the command mapping. The results provide foundational insights into the joint optimization of control and mapping strategies and offer practical guidelines for advancing teleoperation in complex, real-world scenarios.

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Neural networks meet PID control: Revolutionizing manipulator regulation with gravitational compensation

2025 , Marco Moran-Armenta , Jorge Montoya-Cháirez , Francisco G. Rossomando , Emanuel Slawiñski , Vicente Mut , Chicaiza Claudio, Fernando , Javier Moreno-Valenzuela

This research proposes an innovative approach to improve the performance of regulation control systems in manipulators by combining PID control with gravitational compensation using neural networks. In this work, a modified PID control structure that incorporates a gravitational compensation term given by a neural network is introduced, thus allowing a more precise and adaptive response to gravitational and dynamic perturbations of the system. Furthermore, the controller's performance is evaluated through real-time experiments in two manipulators, comparing its performance with the same structure, one without integral action, another without neural compensation and the last one assuming that the gravity vector is known. The results show a significant improvement in system regulation accuracy, demonstrating the proposed controller's effectiveness.

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