TY - JOUR A1 - Salamat, Babak A1 - Elsbacher, Gerhard T1 - Centralized Control in Networks of Underactuated Nonidentical Euler–Lagrange Systems Using a Generalised Multicoordinates Transformation JF - IEEE Access N2 - Controlling the network of underactuated Euler–Lagrange (EL) systems is challenging because of their coupled inertia matrices and time-variant control input matrices. We present generalized multi-coordinates transformation that renders the network of underactuated Euler-Lagrange dynamics in particular forms, whose mechanical properties should be preserved. The network of N nonidentical Euler–Lagrange EL-systems is modeled as a weighted interconnection graph where each EL-system is a node, and the control action at each node is a function of its state and the states of its neighbors. Second, we propose an online optimally centralized control mechanism with the prime objective of energy efficiency. The result is applied to the network of underactuated vertical takeoff and landing aircraft with strong input coupling, including the effect of the weight of the rotors into the dynamical system models. In this regard, we obtain very simple and powerful state-feedback solutions. UR - https://doi.org/10.1109/ACCESS.2022.3178606 KW - Aerospace KW - generalized multi-coordinates transformation KW - network control systems KW - underactuated Euler-Lagrange systems Y1 - 2022 UR - https://doi.org/10.1109/ACCESS.2022.3178606 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-24354 SN - 2169-3536 VL - 10 SP - 58311 EP - 58319 PB - IEEE CY - New York ER - TY - JOUR A1 - Salamat, Babak A1 - Elsbacher, Gerhard T1 - Steering a Swarm of Large-Scale Underactuated Mechanical Systems Using a Generalized Coordinates Transformation JF - Aerospace N2 - Steering large-scale particle or robot systems is challenging because of their high dimensionality. We use a centralized stochastic approach that allows for optimal control at the cost of a central element instead of a decentralized approach. Previous works are often restricted to the assumption of fully actuated robots. Here we propose an approach for underactuated robots that allows for energy-efficient control of the robot system. We consider a simple task of gathering the robots (minimizing positional variance) and steering them towards a goal point within a bounded area without obstacles. We make two main contributions. First, we present a generalized coordinate transformation for underactuated robots, whose physical properties should be considered. We choose Euler-Lagrange systems that describe a large class of robot systems. Second, we propose an optimal control mechanism with the prime objective of energy efficiency. We show the feasibility of our approach in robot simulations. UR - https://doi.org/10.3390/aerospace9110702 KW - aerospace KW - generalized multi-coordinates transformation KW - network control systems KW - underactuated Euler–Lagrange systems Y1 - 2022 UR - https://doi.org/10.3390/aerospace9110702 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-29488 SN - 2226-4310 VL - 9 IS - 11 PB - MDPI CY - Basel ER - TY - JOUR A1 - Salamat, Babak A1 - Elsbacher, Gerhard A1 - Tonello, Andrea M. T1 - Energy Shaping Control in Underactuated Robot Systems with Underactuation Degree Two JF - IEEE Robotics and Automation Letters UR - https://doi.org/10.1109/LRA.2025.3534688 Y1 - 2025 UR - https://doi.org/10.1109/LRA.2025.3534688 SN - 2377-3766 VL - 10 IS - 3 SP - 2734 EP - 2741 PB - IEEE CY - New York ER - TY - JOUR A1 - Zieher, Simon A1 - Olcay, Ertug A1 - Kefferpütz, Klaus A1 - Salamat, Babak A1 - Olzem, Sebastian-Sven A1 - Elsbacher, Gerhard A1 - Meeß, Henri T1 - Drones for automated parcel delivery: Use case identification and derivation of technical requirements JF - Transportation Research Interdisciplinary Perspectives N2 - Drone-based parcel delivery is a rapidly growing domain posing many technological and operational challenges. Drone technologies have been under increasing levels of investigation and development over the past years. Since the realization of drone-based delivery can only be economically feasible at large scales, it requires processes that address the outstanding challenges holistically. However, the majority of research focuses on individual aspects such as environmental perception, route planning, operational design, and business models without addressing the challenges in the overall system. This paper conducts a quantitative analysis of the requirements for identified use cases that are considered relevant for the upcoming future. We provide a comprehensive technology overview and derive requirements and specifications for the targeted use cases that are not fulfilled by the current state-of-the-art. The use cases are not only related to last-mile delivery but also long-distance (hub-to-hub) logistics as well as courier and express delivery. UR - https://doi.org/10.1016/j.trip.2024.101253 Y1 - 2024 UR - https://doi.org/10.1016/j.trip.2024.101253 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-53303 SN - 2590-1982 VL - 2024 IS - 28 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Salamat, Babak A1 - Elsbacher, Gerhard A1 - Tonello, Andrea M. A1 - Belzner, Lenz T1 - Model-Free Distributed Reinforcement Learning State Estimation of a Dynamical System Using Integral Value Functions JF - IEEE Open Journal of Control Systems UR - https://doi.org/10.1109/OJCSYS.2023.3250089 Y1 - 2023 UR - https://doi.org/10.1109/OJCSYS.2023.3250089 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-43492 SN - 2694-085X VL - 2 SP - 70 EP - 78 PB - IEEE CY - Piscataway ER - TY - JOUR A1 - Salamat, Babak A1 - Yaghmaei, Abolfazl A1 - Elsbacher, Gerhard A1 - Tonello, Andrea M. A1 - Yazdanpanah, Mohammad Javad T1 - An Innovative Control Design Procedure for Under-Actuated Mechanical Systems: Emphasizing Potential Energy Shaping and Structural Preservation JF - IEEE Open Journal of Control Systems N2 - In this paper, we propose a procedure to solve the controlled design for a class of underactuated mechanical systems. Our proposed method can be viewed as a sub-method of the IDA-PBC or Controlled Lagrangian approaches, with a particular focus on shaping the potential energy. By emphasizing potential energy shaping, we can effectively tackle the bottleneck presented by the matching equation in these approaches. Moreover, our method leverages a suitable coordinate transformation that is inspired by the physics of the system, further enhancing its efficacy. Therefore, our design procedure is based on a coordinate transformation plus potential energy shaping in the new coordinates, and its existence and possibility of potential energy shaping can be verified via some algebraic calculations, making it constructive. To illustrate the results, we consider the cart-pole system and a recently introduced underactuated mechanical system named swash mass pendulum (SMP) [1]. The SMP consists of a pendulum made of a rigid shaft connected to a pair of cross-shafts where two swash masses can move under the action of servo-mechanisms. UR - https://doi.org/10.1109/OJCSYS.2023.3320512 KW - Controller design KW - under-actuated mechanical systems KW - Euler-Lagrange dynamics KW - potential matching equation Y1 - 2023 UR - https://doi.org/10.1109/OJCSYS.2023.3320512 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-40295 SN - 2694-085X VL - 2 SP - 356 EP - 365 PB - IEEE CY - New York ER - TY - JOUR A1 - Salamat, Babak A1 - Olzem, Sebastian-Sven A1 - Elsbacher, Gerhard A1 - Tonello, Andrea M. T1 - Global Multi-Phase Path Planning Through High-Level Reinforcement Learning JF - IEEE Open Journal of Control Systems N2 - In this paper, we introduce the Global Multi-Phase Path Planning ( GMP3 ) algorithm in planner problems, which computes fast and feasible trajectories in environments with obstacles, considering physical and kinematic constraints. Our approach utilizes a Markov Decision Process (MDP) framework and high-level reinforcement learning techniques to ensure trajectory smoothness, continuity, and compliance with constraints. Through extensive simulations, we demonstrate the algorithm's effectiveness and efficiency across various scenarios. We highlight existing path planning challenges, particularly in integrating dynamic adaptability and computational efficiency. The results validate our method's convergence guarantees using Lyapunov’s stability theorem and underscore its computational advantages. UR - https://doi.org/10.1109/OJCSYS.2024.3435080 Y1 - 2024 UR - https://doi.org/10.1109/OJCSYS.2024.3435080 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-52776 SN - 2694-085X VL - 3 SP - 405 EP - 415 PB - IEEE CY - Piscataway ER - TY - JOUR A1 - Salamat, Babak A1 - Bencic, Daniel A1 - Elsbacher, Gerhard A1 - Seidel, Christian A1 - Tonello, Andrea M. T1 - Investigating Integral Reinforcement Learning to Achieve Asymptotic Stability in Underactuated Mechanical Systems JF - IEEE Robotics and Automation Letters UR - https://doi.org/10.1109/LRA.2023.3332556 Y1 - 2023 UR - https://doi.org/10.1109/LRA.2023.3332556 SN - 2377-3766 VL - 9 IS - 1 SP - 191 EP - 198 PB - IEEE CY - New York ER - TY - JOUR A1 - Salamat, Babak A1 - Mattern, Dominik A1 - Olzem, Sebastian-Sven A1 - Elsbacher, Gerhard A1 - Seidel, Christian A1 - Tonello, Andrea M. T1 - GMP3: Learning-Driven, Bellman-Guided Trajectory Planning for AAVs in Real-Time on SE(3) JF - IEEE Access N2 - We propose GMP3, a multiphase global path planning framework that generates dynamically feasible three-dimensional trajectories for unmanned aerial vehicles (UAVs) operating in cluttered environments. The framework extends traditional path planning from Euclidean position spaces to the Lie group SE(3), allowing joint learning of translational motion and rotational dynamics. A modified Bellman-based operator is introduced to support reinforcement learning (RL) policy updates while leveraging prior trajectory information for improved convergence. GMP3 is designed as a distributed framework in which agents influence each other and share policy information along the trajectory: each agent refines its assigned segment and shares with its neighbors via a consensus-based scheme, enabling cooperative policy updates and convergence toward a path shaped globally even under kinematic constraints.We also propose DroneManager, a modular ground control software that interfaces the planner with real UAVs platforms via the Micro Air Vehicle Link (MAVLink) protocol, supporting real-time deployment and feedback. Simulation studies and indoor flight experiments validate the effectiveness of the proposed method in constrained 3D environments, demonstrating reliable obstacle avoidance and smooth, feasible trajectories across both position and orientation. UR - https://doi.org/10.1109/ACCESS.2026.3661193 Y1 - 2026 UR - https://doi.org/10.1109/ACCESS.2026.3661193 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-66826 SN - 2169-3536 VL - 14 SP - 22720 EP - 22733 PB - IEEE CY - New York ER -