Decentralized Geometric Control for Cable-Suspended Payload Transport with Adaptive Mass Estimation

Jul 16, 2026

Cooperative aerial transport demands controllers that respect nonlinear manifold geometry, avoid centralized coordination, ensure operational safety, and remain robust to disturbances. The document introduces GPAC, a four-layer hierarchical framework for N quadrotors to carry a cable-suspended payload without a central coordinator and without exchanging cable states or adaptive parameters. Each agent infers effective load share from local cable measurements, reconstructs payload position from cable geometry, and communicates only low-rate neighbor position for collision avoidance. The approach combines geometric position/attitude control, anti-swing regulation, an extended-state observer for wind rejection, concurrent learning-based mass estimation without persistent excitation, and a priority-ordered CBF-inspired safety filter with ISSf margins and compatibility with SO(3) stability. High-fidelity simulations report 33.8 cm mean payload-tracking RMSE with low computation cost.

LanguageEnglish

CategoryResearch & Report

FormatPDF

Pages11

Reading Time28 min

Abstract

Introduction

Motivation and safety-critical challenges

Related geometric and distributed approaches

Control barrier functions and stability needs

Decentralized Geometric Control for Cable-Suspended Payload Transport with Adaptive Mass Estimation Hadi Hajieghrary 1 , Benedikt Walter2 , Paul Schmitt3 , and Miguel Hurtado4 arXiv :2607 .00024v1 [ cs .RO] 20 Jun 2026 Abstract—Cooperative aerial transport requires controllers that respect nonlinear manifold geometry, operate without centralized coordination, and respect operational safety constraints. To address these demands, we present GPAC, a four-layer hierarchical architecture enabling N quadrotors to transport a cablesuspended payload without a central coordinator and without exchanging cable states or adaptive parameters. The key insight is implicit coordination: each quadrotor independently estimates its effective load share from local cable measurements, so combined forces converge to the correct total, even without knowledge of N or the payload mass; the payload position is reconstructed locally from each agent’s own cable geometry, and the only interagent communication is a low-rate neighbor-position broadcast for collision avoidance. GPAC operates directly on the full nonlinear configuration manifold and integrates geometric position and attitude control, anti-swing regulation, an extended-state observer for wind rejection, concurrent learning-based mass estimation without persistent excitation, and a priority-ordered control barrier function (CBF)-inspired safety filter that reduces operational risk, with input-to-state safety (ISSf) margins that hold exactly under single-constraint activation. A compatibility result shows that the filter’s force modifications keep the desired attitude within the almost-global stability region of the SO(3) attitude controller. Finally, high-fidelity simulation with flexible cables, onboard sensor fusion, and wind turbulence—with all control and estimation loops closed through the estimator—yields a 33.8 cm mean payload-tracking RMSE (2.8% coefficient of variation over 13 seeds) at a low per-agent computational cost. Index Terms—Cooperative aerial transport, geometric control, decentralized systems, adaptive estimation, control barrier functions, multi-UAV systems. I. INTRODUCTION Cooperative aerial transport involves several unmanned aerial vehicles (UAVs) working together to carry a payload with cables. This approach offers greater capacity, a larger workspace, and better fault tolerance than using a single UAV. However, these systems are safety-critical. Issues such as cableslack, excessive swing, vehicle tilt, collisions between UAVs, and disturbances can all cause loss of control or make the payload unstable. To achieve cooperation among N quadrotors, controllers must handle the nonlinear system dynamics, operate without centralized coordination, and address the main failure modes. Lee, Sreenath, and Kumar [1], [2] developed a method for cable-suspended transport using the full nonlinear con- 1 Hadi Hajieghrary ([hadi.hajieghrary@gatech.edu](hadi.hajieghrary@gatech.edu)), 2 Benedikt Walter ([walter.benedikt@gmail.com](walter.benedikt@gmail.com)), 3 Paul Schmitt ([pauls@massrobotics.org](pauls@massrobotics.org)), and 4 Miguel Hurtado ([miguel.hurtadomit@gmail.com](miguel.hurtadomit@gmail.com)) prepared this manuscript and present it solely in their individual capacities. The views expressed in this paper are those of the authors and do not necessarily reflect the views of their employers or affiliated organizations. figuration manifold, achieving almost-global stability without issues arising from Euler-angle singularities. Later, they added anti-swing control for the cables [3] . Sharma and Sundaram [4] created a geometric controller for multiUAV payload transfer that does not need link information. Sun et al. [5] showed agile cooperative cable manipulation with online kinodynamic planning. A differential-geometric constrained-mechanics framework earlier modeled cooperative cable towing—holonomic cable constraints coupled to nonholonomic vehicle dynamics—and

FAQs

How does GPAC handle safety constraints during operation?

A priority-ordered CBF-inspired safety filter makes minimal modifications to the main controller while maintaining input-to-state safety (ISSf) margins under single-constraint activation, and it is compatible with the SO(3) attitude controller’s almost-global stability region.

Jul 16, 2026

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