Forceful Aerial Manipulation based on an Aerial Robotic Chain: Hybrid Modeling and Control @autonomousrobotslab

Uploaded October 2020 | Updated September 2026, 3 weeks ago

This paper presents the system design, modeling, and control of the Aerial Robotic Chain Manipulator. This new robot design offers the potential to exert strong forces and moments to the environment, carry and lift significant payloads, and simultaneously navigate through narrow corridors. We contribute a hybrid modeling framework to model the system both in Free-flight mode, where the end-effector acts as a normal pendulum, and Aerial Manipulation mode, where the system behaves as an inverted pendulum. Respective controllers are designed for both operating modes with stability guarantees provided by Lyapunov theory. The presented experimental studies include a valve rotation task, a pick-and-release task, and the verification of load oscillation suppression to demonstrate the stability and performance of the system.

Forceful Aerial Manipulation based on an Aerial Robotic Chain: Hybrid Modeling and Control

$ICRA2022 Talk Autonomous Teamed Exploration of Subterranean Environments with Legged & Aerial Robots ICRA 2022 Talk on our paper: Mihir Kulkarni, Mihir Rahul Dharmadhikari, Marco Tranzatto, Samuel Zimmermann, Victor Reijgwart, Paolo De Petris, Huan Nguyen, Nikhil Vijay Khedekar, Christos Papachristos, Lionel Ott, Roland Siegwart, Marco Hutter, Kostas Alexis, Autonomous Teamed Exploration of Subterranean Environments using Legged and Aerial Robots, IEEE International Conference on Robotics and Automation (ICRA), May 23-27, 2022, Philadelphia (PA), USA Abstract: This paper presents a novel strategy for autonomous teamed exploration of subterranean environments using legged and aerial robots. Tailored to the fact that subterranean settings, such as cave networks and underground mines, often involve complex, large-scale and multi-branched topologies, while wireless communication within them can be particularly challenging, this work is structured around the synergy of an onboard exploration path planner that allows for resilient long-term autonomy, and a multi-robot coordination framework. The onboard path planner is unified across legged and flying robots and enables navigation in environments with steep slopes, and diverse geometries. When a communication link is available, each robot of the team shares submaps to a centralized location where a multi-robot coordination framework identifies global frontiers of the exploration space to inform each system about where it should re-position to best continue its mission. The strategy is verified through a field deployment inside an underground mine in Switzerland using a legged and a flying robot collectively exploring for $45textrm{ min}$, as well as a longer simulation study with three systems. GBPlanner 2 Open-Source release: https://github.com/ntnu-arl/gbplanner_ros$

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