Michael Pantic


Last Name

Pantic

First Name

Michael

ORCID

0000-0002-2410-5152

Organisational unit

03737 - Siegwart, Roland Y. / Siegwart, Roland Y.

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2019 - 201922020 - 202529
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Publications1 - 10 of 31
  • The ETH-MAV Team in the MBZ International Robotics Challenge
    Item type: Journal Article
    Bähnemann, Rik; Pantic, Michael; Popović, Marija; et al. (2019)
    Journal of Field Robotics
  • Trajectory Tracking Nonlinear Model Predictive Control for an Overactuated MAV
    Item type: Conference Paper
    Brunner, Maximilian; Bodie, Karen; Kamel, Mina; et al. (2020)
    2020 IEEE International Conference on Robotics and Automation (ICRA)
    This work presents a method to control omnidirectional micro aerial vehicles (OMAVs) for the tracking of 6-DoF trajectories in free space. A rigid body model based approach is applied in a receding horizon fashion to generate optimal wrench commands that can be constrained to meet limits given by the mechanical design and actuators of the platform. Allocation of optimal actuator commands is performed in a separate step. A disturbance observer estimates forces and torques that may arise from unmodeled dynamics or external disturbances and fuses them into the optimization to achieve offset-free tracking. Experiments on a fully overactuated MAV show the tracking performance and compare it against a classical PD-based controller. © 2020 IEEE.
  • An Efficient Sampling-Based Method for Online Informative Path Planning in Unknown Environments
    Item type: Journal Article
    Schmid, Lukas; Pantic, Michael; Khanna, Raghav; et al. (2020)
    IEEE Robotics and Automation Letters
  • Reactive Motion Planning for Rope Manipulation and Collision Avoidance using Aerial Robots
    Item type: Conference Paper
    Shi, Liping; Pantic, Michael; Andersson, Olov; et al. (2022)
    2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
    In this work we address the challenging problem of manipulating a flexible link, like a rope, with an aerial robot. Inspired by spraying tasks in construction and maintenance scenarios, we consider the case in which an autonomous end-effector (e.g., a spray nozzle moved by a robot or a human operator) is connected to a fixed point by a rope (e.g., a hose). To avoid collisions between the rope and the environment while the end-effector moves, we propose the use of an aerial robot as a flying companion to properly manipulate the rope away from collisions. The aerial robot is attached to the rope between the end-effector and the fixed point. Assuming no direct control of the end-effector (e.g., when operated by a human), we design a reactive and fast motion planner for the aerial robot. Grounding on the theory of Forced Geometric Fabrics, we design a motion planner that generates trajectories to drive the aerial robot to follow the end-effector, while manipulating the rope to avoid collisions in cluttered environments. To include the complex behavior of the flexible link, we propose a rope model that estimates its real-time state under forces and position-based interactions, as well as collisions with obstacle surfaces. Finally, we evaluate the system behavior and the motion planner performance in simulations, as well as in real-world experiments on an original spray painting application.
  • Chasing millimeters: design, navigation and state estimation for precise in-flight marking on ceilings
    Item type: Journal Article
    Lanegger, Christian; Pantic, Michael; Bähnemann, Rik; et al. (2023)
    Autonomous Robots
    Precise markings for drilling and assembly are crucial, laborious construction tasks. Aerial robots with suitable end-effectors are capable of markings at the millimeter scale. However, so far, they have only been demonstrated under laboratory conditions where rigid state estimation and navigation assumptions do not impede robustness and accuracy. This paper presents a complete aerial layouting system capable of precise markings on-site under realistic conditions. We use a compliant actuated end-effector on an omnidirectional flying base. Combining a two-stage factor-graph state estimator with a Riemannian Motion Policy-based navigation stack, we avoid the need for a globally consistent state estimate and increase robustness. The policy-based navigation is structured into individual behaviors in different state spaces. Through a comprehensive study, we show that the system creates highly precise markings at a relative precision of 1.5 mm and a global accuracy of 5-6 mm and discuss the results in the context of future construction robotics.
  • Flying corrosion inspection robot for corrosion monitoring of bridges
    Item type: Other Conference Item
    Pfändler, Patrick; Bodie, Karen; Pantic, Michael; et al. (2024)
  • Active Interaction Force Control for Contact-Based Inspection with a Fully Actuated Aerial Vehicle
    Item type: Journal Article
    Bodie, Karen; Brunner, Maximilian; Pantic, Michael; et al. (2021)
    IEEE Transactions on Robotics
    This article presents and validates active interaction force control and planning for fully actuated and omnidirectional aerial manipulation platforms, with the goal of aerial contact inspection in unstructured environments. We present a variable axis-selective impedance control which integrates direct force control for intentional interaction, using feedback from an on-board force sensor. The control approach aims to reject disturbances in free flight, while handling unintentional interaction and actively controlling desired interaction forces. A fully actuated and omnidirectional tilt-rotor aerial system is used to show capabilities of the control and planning methods. Experiments demonstrate disturbance rejection, push-and-slide interaction, and force-controlled interaction in different flight orientations. The system is validated as a tool for nondestructive testing of concrete infrastructure, and statistical results of interaction control performance are presented and discussed.
  • Aerial Robots on Glaciers
    Item type: Presentation
    Pantic, Michael (2022)
  • Pushing the Limits of Reactive Navigation: Learning to Escape Local Minima
    Item type: Journal Article
    Meijer, Isar; Pantic, Michael; Oleynikova, Helen; et al. (2025)
    IEEE Robotics and Automation Letters
    Can a robot navigate a cluttered environment without an explicit map? Reactive methods that use only the robot's current sensor data and local information are fast and flexible, but prone to getting stuck in local minima. Is there a middle-ground between reactive methods and map-based path planners? In this paper, we investigate feed forward and recurrent networks to augment a purely reactive sensor-based navigation algorithm, which should give the robot "geometric intuition" about how to escape local minima. We train on a large number of extremely cluttered simulated worlds, auto-generated from primitive shapes, and show that our system zero-shot transfers to worlds based on real data 3D man-made environments, and can handle up to 30% sensor noise without degradation of performance. We also offer a discussion of what role network memory plays in our final system, and what insights can be drawn about the nature of reactive vs. map-based navigation.
  • Demo of Aerial Robot Worker
    Item type: Presentation
    Pantic, Michael; Girod, Rik (2022)
Publications1 - 10 of 31