Lennart Werner


Last Name

Werner

First Name

Lennart

ORCID

0000-0002-1338-0458

Organisational unit

09570 - Hutter, Marco / Hutter, Marco

Filters

2024 - 20254
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Publications 1 - 4 of 4
  • Dynamic Throwing with Robotic Material Handling Machines
    Item type: Conference Paper
    Werner, Lennart; Nan, Fang; Eyschen, Pol; et al. (2024)
    2024 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
    Automation of hydraulic material handling machinery is currently limited to semi-static pick-and-place cycles. Dynamic throwing motions which utilize the passive joints, can greatly improve time efficiency as well as increase the dumping workspace. In this work, we use Reinforcement Learning (RL) to design dynamic controllers for material handlers with underactuated arms as commonly used in logistics. The controllers are tested both in simulation and in real-world experiments on a 12-ton test platform. The method is able to exploit the passive joints of the gripper to perform dynamic throwing motions. With the proposed controllers, the machine is able to throw individual objects to targets outside the static reachability zone with good accuracy for its practical applications. The work demonstrates the possibility of using RL to perform highly dynamic tasks with heavy machinery, suggesting a potential for improving the efficiency and precision of autonomous material handling tasks.
  • Calibrated dynamic modeling for force and payload estimation in hydraulic machinery
    Item type: Journal Article
    Werner, Lennart; Eyschen, Pol; Costello, Sean; et al. (2025)
    Construction Robotics
    Accurate real-time estimation of end effector interaction forces in hydraulic excavators is a key enabler for advanced auto mation in heavy machinery. Accurate knowledge of these forces allows improved, precise grading and digging maneuvers. To address these challenges, we introduce a high-accuracy, retrofittable 2D force- and payload estimation algorithm that does not impose additional requirements on the operator regarding trajectory, acceleration or the use of the slew joint. The approach is designed for retrofittability, requires minimal calibration and no prior knowledge of machine-specific dynamic characteristics. Specifically, we propose a method for identifying a dynamic model, necessary to estimate both end effector interaction forces and bucket payload during normal operation. Our optimization-based payload estimation achieves a full-scale payload accuracy of 1%. On a standard 25 t excavator, the online force measurement from pres sure and inertial measurements achieves a direction accuracy of 13° and a magnitude accuracy of 383 N. The method’s accuracy and generalization capability are validated on two excavator platforms of different type and weight classes. We benchmark our payload estimation against a classical quasistatic method and a commercially available system. Our system outperforms both in accuracy and precision.
  • Direction Finding for Software Defined Radios with Switched Uniform Circular Arrays
    Item type: Conference Paper
    Werner, Lennart; Gardill, Markus; Hutter, Marco (2025)
    2025 IEEE/MTT-S International Microwave Symposium - IMS 2025
    Accurate Direction of Arrival (DoA) estimation is critical for applications in robotics and communication, but high costs and complexity of coherent multi-channel receivers hinder accessibility. This work proposes a cost-effective DoA estimation system for continuous wave (CW) signals in the 2.4 GHz ISM band. A two-channel software-defined radio (SDR) with time-division multiplexing (TDM) enables pseudo-coherent sampling of an eight-element uniform circular array (UCA) with low hardware complexity. A central reference antenna mitigates phase jitter and sampling errors. The system applies an enhanced MUSIC algorithm with spatial smoothing to handle light multipath interference in indoor and outdoor environments. Experiments in an anechoic chamber validate accuracy under ideal conditions, while real-world tests confirm robust performance in multipath-prone scenarios. With 5 Hz DoA updates and post-processing to enhance tracking, the system provides an accessible and reliable solution for DoA estimation in real-world environments.
  • Obstacle-Avoidant Leader Following with a Quadruped Robot
    Item type: Conference Paper
    Scheidemann, Carmen; Werner, Lennart; Reijgwart, Victor; et al. (2025)
    2025 IEEE International Conference on Robotics and Automation (ICRA)
    Personal mobile robotic assistants are expected to find wide applications in industry and healthcare. For example, people with limited mobility can benefit from robots helping with daily tasks, or construction workers can have robots perform precision monitoring tasks on-site. However, manually steering a robot while in motion requires significant concentration from the operator, especially in tight or crowded spaces. This reduces walking speed, and the constant need for vigilance increases fatigue and, thus, the risk of accidents. This work presents a virtual leash with which a robot can naturally follow an operator. We use a sensor fusion based on a custom-built RF transponder, RGB cameras, and a LiDAR. In addition, we customize a local avoidance planner for legged platforms, which enables us to navigate dynamic and narrow environments. We successfully validate on the ANYmal platform [1] the robustness and performance of our entire pipeline in real-world experiments. The video is available at: obstacle-avoidant-leader-following.
Publications 1 - 4 of 4