mlsanityData to 14 Oct 2026

Reinforcement Learning Position Control of a Quadrotor Using Soft Actor-Critic (SAC)

arXiv 2512.18333 ↗First posted 20 Dec 2025cs.RO cs.AI cs.LGcited by 2

On the map: Deep reinforcement learning methods → RL for robot navigation and UAV control

Abstract (arXiv)

This paper proposes a new Reinforcement Learning (RL) based control architecture for quadrotors. With the literature focusing on controlling the four rotors' RPMs directly, this paper aims to control the quadrotor's thrust vector. The RL agent computes the percentage of overall thrust along the quadrotor's z-axis along with the desired Roll (φ) and Pitch (θ) angles. The agent then sends the calculated control signals along with the current quadrotor's Yaw angle (psi) to an attitude PID controller. The PID controller then maps the control signals to motor RPMs. The Soft Actor-Critic algorithm, a model-free off-policy stochastic RL algorithm, was used to train the RL agents. Training results show the faster training time of the proposed thrust vector controller in comparison to the conventional RPM controllers. Simulation results show smoother and more accurate path-following for the proposed thrust vector controller.

Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Placed in RL for robot navigation and UAV control, one of 15 directions in Deep reinforcement learning methods. Builds on 2 of its 5 references that are in the map. First posted on arXiv 20 Dec 2025.

Builds on

2 of 5 references.

References · 2

  1. 2020Using Soft Actor-Critic for Low-Level UAV Controlcited by 5
  2. 2021A Model-free Deep Reinforcement Learning Approach To Maneuver A Quadrotor Despite Single Rotor Failurecited by 2

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 2.

2 papers.

  1. 2026A Heuristic Approach for Performance Tuning in RL-based Quadrotor Control via Reward Design and Termination Conditionscited by 0
  2. 2026Network Distributed Multi-Agent Reinforcement Learning for Consensus Control of Quadcopterscited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2025Reinforcement Learning Based Prediction of PID Controller Gains for Quadrotor UAVs
  2. 2025Leveling the Playing Field: Carefully Comparing Classical and Learned Controllers for Quadrotor Trajectory Tracking
  3. 2026Learning End-to-End Control for Omnidirectional Aerial Motion on Overactuated Tilt-rotor Quadrotors
  4. 2026Online Reinforcement Learning for Safe Gain Scheduling in Nonlinear Quadrotor Control
  5. 2024Multi-Task Reinforcement Learning for Quadrotors
  6. 2025RAPTOR: A Foundation Policy for Quadrotor Control
  7. 2026Adaptive Outer-Loop Control of Quadrotors via Reinforcement Learning
  8. 2026Design of Adaptive PID Controller Based On Asynchronous Advantage Actor Critic Learning Method for QuadCopter Control ↗