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Thrust Microstepping via Acceleration Feedback in Quadrotor Control for Aerial Grasping of Dynamic Payload

Ashish Kumar, Laxmidhar Behera

TL;DR

This work tackles the challenge of aerial grasping with off-center, dynamically attached payloads by presenting TMDC, an end-to-end control framework that combines Thrust Microstepping via Acceleration Feedback (TMAF) with Decoupled Motion Control (DMC). TMAF computes thrust from acceleration error using microsteps, avoiding explicit dependence on mass or gravity and remaining responsive at low loop rates, while DMC separates vertical and horizontal dynamics to counteract disturbances from dynamic payloads. The approach yields substantial stability and accuracy gains, achieving RMSEs around $0.04\,$m in center/off-center payload tests and outperforming Direct Acceleration (DA) and Geometric Tracking (GT) in challenging real-world scenarios, including onboard SLAM at $30$ Hz and non-uniform loop rates. Practically, TMDC enables reliable takeoff, hover, and landing in constrained indoor spaces, robust trajectory execution, and resilience to battery aging and wind, making aerial grasping with dynamic payloads more viable for real deployments.

Abstract

In this work, we propose an end-to-end Thrust Microstepping and Decoupled Control (TMDC) of quadrotors. TMDC focuses on precise off-centered aerial grasping of payloads dynamically, which are attached rigidly to the UAV body via a gripper contrary to the swinging payload. The dynamic payload grasping quickly changes UAV's mass, inertia etc, causing instability while performing a grasping operation in-air. We identify that to handle unknown payload grasping, the role of thrust controller is crucial. Hence, we focus on thrust control without involving system parameters such as mass etc. TMDC is based on our novel Thrust Microstepping via Acceleration Feedback (TMAF) thrust controller and Decoupled Motion Control (DMC). TMAF precisely estimates the desired thrust even at smaller loop rates while DMC decouples the horizontal and vertical motion to counteract disturbances in the case of dynamic payloads. We prove the controller's efficacy via exhaustive experiments in practically interesting and adverse real-world cases, such as fully onboard state estimation without any positioning sensor, narrow and indoor flying workspaces with intense wind turbulence, heavy payloads, non-uniform loop rates, etc. Our TMDC outperforms recent direct acceleration feedback thrust controller (DA) and geometric tracking control (GT) in flying stably for aerial grasping and achieves RMSE below 0.04m in contrast to 0.15m of DA and 0.16m of GT.

Thrust Microstepping via Acceleration Feedback in Quadrotor Control for Aerial Grasping of Dynamic Payload

TL;DR

This work tackles the challenge of aerial grasping with off-center, dynamically attached payloads by presenting TMDC, an end-to-end control framework that combines Thrust Microstepping via Acceleration Feedback (TMAF) with Decoupled Motion Control (DMC). TMAF computes thrust from acceleration error using microsteps, avoiding explicit dependence on mass or gravity and remaining responsive at low loop rates, while DMC separates vertical and horizontal dynamics to counteract disturbances from dynamic payloads. The approach yields substantial stability and accuracy gains, achieving RMSEs around m in center/off-center payload tests and outperforming Direct Acceleration (DA) and Geometric Tracking (GT) in challenging real-world scenarios, including onboard SLAM at Hz and non-uniform loop rates. Practically, TMDC enables reliable takeoff, hover, and landing in constrained indoor spaces, robust trajectory execution, and resilience to battery aging and wind, making aerial grasping with dynamic payloads more viable for real deployments.

Abstract

In this work, we propose an end-to-end Thrust Microstepping and Decoupled Control (TMDC) of quadrotors. TMDC focuses on precise off-centered aerial grasping of payloads dynamically, which are attached rigidly to the UAV body via a gripper contrary to the swinging payload. The dynamic payload grasping quickly changes UAV's mass, inertia etc, causing instability while performing a grasping operation in-air. We identify that to handle unknown payload grasping, the role of thrust controller is crucial. Hence, we focus on thrust control without involving system parameters such as mass etc. TMDC is based on our novel Thrust Microstepping via Acceleration Feedback (TMAF) thrust controller and Decoupled Motion Control (DMC). TMAF precisely estimates the desired thrust even at smaller loop rates while DMC decouples the horizontal and vertical motion to counteract disturbances in the case of dynamic payloads. We prove the controller's efficacy via exhaustive experiments in practically interesting and adverse real-world cases, such as fully onboard state estimation without any positioning sensor, narrow and indoor flying workspaces with intense wind turbulence, heavy payloads, non-uniform loop rates, etc. Our TMDC outperforms recent direct acceleration feedback thrust controller (DA) and geometric tracking control (GT) in flying stably for aerial grasping and achieves RMSE below 0.04m in contrast to 0.15m of DA and 0.16m of GT.
Paper Structure (43 sections, 13 equations, 18 figures, 3 tables)

This paper contains 43 sections, 13 equations, 18 figures, 3 tables.

Table of Contents

  1. Introduction
  2. Quadrotor System and Nomenclature
  3. Thrust Microstepping
  4. Microstepper Controller
  5. Microstepped Thrust Estimation
  6. Structural Analysis of TMAF and State-of-the-art
  7. Absence of Mass and Gravity
  8. Absence of Error Integral
  9. Rapid Acceleration Changes
  10. TMAF in Aerial Manipulation
  11. Thrust Microstepped Decoupled Control
  12. Position Feedback Loop
  13. Position Controller
  14. Velocity Controller
  15. Decoupled Motion Controller (DMC)
  16. ...and 28 more sections

Figures (18)

  • Figure 1: Left: Our aerial manipulator. Right: TMDC controlling a very large sized quadrotor ($1.30$m$\times0.90$m$\times0.45$m) within a workspace clearance of $10$cm at a very small altitude of $0.5$m, a quite adverse and dangerous practice considering the large sized quadrotor.
  • Figure 2: Quadrotor reference frames.
  • Figure 3: Effect of a sudden force of $12$N in $\bm z_W$ onto the $z, v_z, a_z$ of the quadrotor. Noticeably, the acceleration signal captures a detailed profile of this event, while position and velocity signals do not.
  • Figure 4: Thrust intensity ($f^\star_B$) and microsteps ($\Delta \Gamma$) output of TMAF.
  • Figure 5: Thrust Microstepping via Acceleration Feedback (TMAF) vs Direct Acceleration (DA) Feedback direct and Model Inversion uavmodelling.
  • ...and 13 more figures