Exploiting Different Symmetries for Trajectory Tracking Control with Application to Quadrotors
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Abstract (arXiv)
High performance trajectory tracking control of quadrotor vehicles is an important challenge in aerial robotics. Symmetry is a fundamental property of physical systems and offers the potential to provide a tool to design high-performance control algorithms. We propose a design methodology that takes any given symmetry, linearises the associated error in a single set of coordinates, and uses LQR design to obtain a high performance control; an approach we term Equivariant Regulator design. We show that quadrotor vehicles admit several different symmetries: the direct product symmetry, the extended pose symmetry and the pose and velocity symmetry, and show that each symmetry can be used to define a global error. We compare the linearised systems via simulation and find that the extended pose and pose and velocity symmetries outperform the direct product symmetry in the presence of large disturbances. This suggests that choices of equivariant and group affine symmetries have improved linearisation error.
Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). First posted on arXiv 11 Jul 2022.
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Citing papers per year: 2023: 2; 2024: 1; 2025: 1.
4 papers.
- 2024Leveraging Symmetry to Accelerate Learning of Trajectory Tracking Controllers for Free-Flying Robotic Systemscited by 2
- 2023Can Euclidean Symmetry be Leveraged in Reinforcement Learning and Planning?cited by 1
- 2025Symmetries-enhanced Multi-Agent Reinforcement Learningcited by 1
- 2023Regret Analysis of Online LQR Control via Trajectory Prediction and Tracking: Extended Versioncited by 0
- 2025Symmetries-enhanced Multi-Agent Reinforcement Learning2 Jan 2025
- 2024Leveraging Symmetry to Accelerate Learning of Trajectory Tracking Controllers for Free-Flying Robotic Systems17 Sep 2024
- 2023Can Euclidean Symmetry be Leveraged in Reinforcement Learning and Planning?17 Jul 2023
- 2023Regret Analysis of Online LQR Control via Trajectory Prediction and Tracking: Extended Version21 Feb 2023