Das, Hemjyoti (TU Wien), Vu, Minh Nhat (Automation & Control Institute (ACIN), TU Wien, Austria), Ott, Christian (TU Wien)

Learning Swing-Up Maneuvers for a Suspended Aerial Manipulation Platform in a Hierarchical Control Framework

Scheduled for presentation during the Regular Session "Aerial and Space Robots" (WeBT4), Wednesday, July 16, 2025, 15:00−15:20, Room 108

Joint 10th IFAC Symposium on Mechatronic Systems and 14th Symposium on Robotics, July 15-18, 2025, Paris, France

This information is tentative and subject to change. Compiled on July 16, 2025

Abstract

In this work, we present a novel approach to augment a model-based control method with a reinforcement learning (RL) agent and demonstrate a swing-up maneuver with a suspended aerial manipulation platform. These platforms are targeted towards a wide range of applications on construction sites involving cranes, with swing-up maneuvers allowing it to perch at a given location, inaccessible with purely the thrust force of the platform. Our proposed approach is based on a hierarchical control framework, which allows different tasks to be executed according to their assigned priorities. An RL agent is then subsequently utilized to adjust the reference set-point of the lower-priority tasks to perform the swing-up maneuver, which is confined in the nullspace of the higher-priority tasks, such as maintaining a specific orientation and position of the end-effector. Our approach is validated using extensive numerical simulation studies.