Grzegorz Malczyk


Last Name

Malczyk

First Name

Grzegorz

ORCID

0000-0002-7574-5598

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2022 - 20244
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Publications 1 - 4 of 4
  • End-Effector Pose Estimation and Control for 3D Printing with Articulated Excavators
    Item type: Conference Paper
    Malczyk, Grzegorz; Hutter, Marco (2023)
    2023 21st International Conference on Advanced Robotics (ICAR)
    We introduce a novel large-scale autonomous mobile manipulator system based on an instrumented and automated construction machine for precise on-site sensing and fabrication. The system is based on an automated hydraulic walking excavator equipped with IMUs and LiDAR units. In this work, we develop the technology to precisely map, localize, and move the printhead in the environment. By fusing GNSS localization with kinematic sensing of the mobile machine and end-effector, we get a globally consistent and locally accurate positioning for in situ robotic construction printing process. Moreover, we present a control approach that enables the excavator to move the end-effector precisely along predefined trajectories. We evaluate the performance of the proposed system in a variety of real-world tests in the field and analyze different sensor modalities and arrangements. Finally, we discuss the potential applications, including the fabrication of non-standard architectural forms and increased safety.
  • Impact printed structures : design systems and construction strategies
    Item type: Conference Paper
    Chadha, Kunaljit; Vasey, Lauren; Kango, Ananya; et al. (2024)
    Fabricate ~ Fabricate 2024
  • Estimation of contact and disturbance forces and interaction force tracking with an aerial manipulator
    Item type: Master Thesis
    Malczyk, Grzegorz (2022)
    Over-actuated MAVs have received growing attention in recent years as they allow for physical interaction with their environment. Most interaction tasks so far have been conducted in controlled laboratory environments with little to no outside disturbances. To perform high-accuracy interaction tasks in outdoor conditions, we need a method to reliably distinguish wrenches (i.e. forces and torques) that arise from interaction at the contact point from those that arise from external disturbances (such as aerodynamic effects from wind). The applicable methods to achieve this depend heavily on the used sensor equipment. Therefore, we propose to use a combination of odometry and force/torque sensors, together with an analytical model of the platform dynamics. Thus we can estimate contact and disturbance wrenches simultaneously. In this project, we present a model-based filtering method, namely Extended Kalman Filter (EKF). Following this, an estimation framework is designed and implemented in simulation and verified on the physical platform. With a combination of a novel (especially for MAVs) hybrid motion-force controller, we enable physical interaction of such vehicles with the environment under the presence of external disturbance. For a contact-based inspection, we provide the platform with two types of manipulators. Initially, we validate our approach with a simple rigid manipulator and subsequently with a delta arm attached to the vehicle. We prove the ability of the entire control framework in real-world experiments. Thus, we verify the quality of the estimates by comparing them to ground-truth measurements and showcasing possible industrial applications.
  • Multi-directional Interaction Force Control with an Aerial Manipulator under External Disturbances
    Item type: Journal Article
    Malczyk, Grzegorz; Brunner, Maximilian; Cuniato, Eugenio; et al. (2023)
    Autonomous Robots
    To improve accuracy and robustness of interactive aerial robots, the knowledge of the forces acting on the platform is of uttermost importance. The robot should distinguish interaction forces from external disturbances in order to be compliant with the firsts and reject the seconds. This represents a challenge since disturbances might be of different nature (physical contact, aerodynamic, modeling errors) and be applied to different points of the robot. This work presents a new extended Kalman filter (EKF) based estimator for both external disturbance and interaction forces. The estimator fuses information coming from the system’s dynamic model and it’s state with wrench measurements coming from a Force-Torque sensor. This allows for robust interaction control at the tool’s tip even in presence of external disturbance wrenches acting on the platform. We employ the filter estimates in a novel hybrid force/motion controller to perform force tracking not only along the tool direction, but from any platform’s orientation, without losing the stability of the pose controller. The proposed framework is extensively tested on an omnidirectional aerial manipulator (AM) performing push and slide operations and transitioning between different interaction surfaces, while subject to external disturbances. The experiments are done equipping the AM with two different tools: a rigid interaction stick and an actuated delta manipulator, showing the generality of the approach. Moreover, the estimation results are compared to a state-of-the-art momentum-based estimator, clearly showing the superiority of the EKF approach.
Publications 1 - 4 of 4