Mike Allenspach

Last Name

Allenspach

First Name

Mike

ORCID

0000-0001-6903-6341

Organisational unit

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

Show all metadata

Search Results

Publications 1 - 10 of 18

Nonlinear model predictive control and guidance for a propeller-tilting hybrid unmanned air vehicle
Allenspach, Mike; Ducard, Guillaume J.J. (2021)
Automatica
Evaluation of Human-Robot Interfaces Based on 2D/3D Visual and Haptic Feedback for Aerial Manipulation
Mellet, Julien; Allenspach, Mike; Cuniato, Eugenio; et al. (2025)
Journal of Intelligent & Robotic Systems
Most telemanipulation systems for aerial robots provide the operator with only 2D screen visual information. The lack of richer information about the robot’s status and environment can limit human awareness and, in turn, task performance. While the pilot’s experience can often compensate for this reduced flow of information, providing richer feedback is expected to reduce the cognitive workload and offer a more intuitive experience overall. This work aims to understand the significance of providing additional pieces of information during aerial telemanipulation, namely (i) 3D immersive visual feedback about the robot’s surroundings through mixed reality (MR) and (ii) 3D haptic feedback about the robot interaction with the environment. To do so, we developed a human-robot interface able to provide this information. First, we demonstrate its potential in a real-world manipulation task requiring sub-centimeter-level accuracy. Then, we evaluate the individual effect of MR vision and haptic feedback on both dexterity and workload through a human subjects study involving a virtual block transportation task. Results show that both 3D MR vision and haptic feedback improve the operator’s dexterity in the considered teleoperated aerial interaction tasks. Nevertheless, pilot experience remains the most significant factor.
Review of designs and flight control techniques of hybrid and convertible VTOL UAVs
Ducard, Guillaume J.J.; Allenspach, Mike (2021)
Aerospace Science and Technology
This paper provides a broad perspective and analysis of the work done in control of hybrid and convertible unmanned aerial vehicles (UAVs) for the main existing designs. These flying machines are capable of vertical take off and landing (VTOL) in helicopter mode and able to transition to high-speed forward flight in airplane mode and vice versa. This paper aims at helping engineers and researchers develop flight control systems for VTOL UAVs. To this end, a historical perspective first shows the technological advances in VTOL aircraft over the years. The main VTOL concepts and state-of-art flight control methods for VTOL UAVs are presented and discussed. This study shows both the common parts and the fundamental differences in the modeling, guidance, control, and control allocation for each hybrid-VTOL-UAV type. The open challenges and the current trends in the field are highlighted. These are namely: 1) augmenting or replacing classical controllers with data-driven methods such as neural networks and machine-learning-based controllers; 2) incorporating as much knowledge of the vehicle as possible into the flight controller, for example through model predictive control or model-based nonlinear controllers; 3) a trend towards finding a unified-control approach valid in all flight modes without the need to switch among flight controllers or to perform predefined-gain scheduling, and 4) the need to mitigate control complexity and available computing resources.
Towards 6DoF Bilateral Teleoperation of an Omnidirectional Aerial Vehicle for Aerial Physical Interaction
Allenspach, Mike; Lawrance, Nicholas; Tognon, Marco; et al. (2022)
2022 International Conference on Robotics and Automation (ICRA)
Task Adaptation in Industrial Human-Robot Interaction: Leveraging Riemannian Motion Policies
Allenspach, Mike; Pantic, Michael; Girod, Rik; et al. (2024)
Robotics: Science and System XX
In real-world industrial environments, modern robots often rely on human operators for crucial decision-making and mission synthesis from individual tasks. Effective and safe collaboration between humans and robots requires systems that can adjust their motion to human intentions, enabling dynamic task planning and adaptation. Addressing the needs of industrial applications, we propose a motion control framework that (i) removes the need for manual control of the robot’s movement; (ii) facilitates the formulation and combination of complex tasks; and (iii) allows the seamless integration of human intent recognition and robot motion planning. For this purpose, we leverage a modular and purely reactive approach for task parametrization and motion generation, embodied by Riemannian Motion Policies. The effectiveness of our method is demonstrated, evaluated and compared to a representative state-of-the-art approach in experimental scenarios, inspired by realistic industrial Human-Robot Interaction settings.
Design and Evaluation of a Mixed Reality-based Human-Robot Interface for Teleoperation of Omnidirectional Aerial Vehicles
Allenspach, Mike; Kotter, Till; Bähnemann, Rik; et al. (2023)
2023 International Conference on Unmanned Aircraft Systems (ICUAS)
Omnidirectional aerial vehicles are an attractive solution for visual inspection tasks that require observations from different views. However, the decisional autonomy of modern robots is limited. Therefore, human input is often necessary to safely explore complex industrial environments. Existing teleoperation tools rely on on-board camera views or 3D renderings of the environment to improve situational awareness. Mixed-Reality (MR) offers an exciting alternative, allowing the user to perceive and control the robot's motion in the physical world. Furthermore, since MR technology is not limited by the hardware constraints of standard teleoperation interfaces, like haptic devices or joysticks, it allows us to explore new reference generation and user feedback methodologies. In this work, we investigate the potential of MR in teleoperating 6DoF aerial robots by designing a holographic user interface (see Fig. 1) to control their translational velocity and orientation. A user study with 13 participants is performed to assess the proposed approach. The evaluation confirms the effectiveness and intuitiveness of our methodology, independent of prior user experience with aerial vehicles or MR. However, prior familiarity with MR improves task completion time. The results also highlight limitation to line-of-sight operation at distances where relevant details in the physical environment can still be visually distinguished.
Model Predictive Control of a Convertible Tiltrotor Unmanned Aerial Vehicle
Allenspach, Mike; Ducard, Guillaume (2020)
2020 28th Mediterranean Conference on Control and Automation (MED)
This paper presents a Model Predictive Control (MPC) based control structure for a convertible Unmanned Aerial Vehicle (UAV) with fixed wings and tiltrotor thrust vectoring. The controller encompasses full flight envelope trajectory tracking, thereby optimally exploiting the aircraft's Vertical Take Off and Landing (VTOL) and cruising-forward flight capabilities. An adaptive control allocation is designed to handle the changing control authorities of the actuators and efficiently distribute the required control actions between propellers, tilt servos and control surfaces. Preliminary simulation results show the feasibility of the proposed control approach. © 2020 IEEE.
Modeling and Control of an Omnidirectional Micro Aerial Vehicle Equipped with a Soft Robotic Arm
Szász, Róbert; Allenspach, Mike; Han, Minghao; et al. (2022)
2022 IEEE 5th International Conference on Soft Robotics (RoboSoft)
Flying manipulators are aerial drones with attached rigid-bodied robotic arms and belong to the latest and most actively developed research areas in robotics. The rigid nature of these arms often lack compliance, flexibility, and smoothness in movement. This work proposes to use a soft-bodied robotic arm attached to an omnidirectional micro aerial vehicle (OMAV) to leverage the compliant and flexible behavior of the arm, while remaining maneuverable and dynamic thanks to the omnidirectional drone as the floating base. The unification of the arm with the drone poses challenges in the modeling and control of such a combined platform; these challenges are addressed with this work. We propose a unified model for the flying manipulator based on three modeling principles: the Piecewise Constant Curvature (PCC) and Augmented Rigid Body Model (ARBM) hypotheses for modeling soft continuum robots and a floating-base approach borrowed from the traditional rigid-body robotics literature. To demonstrate the validity and usefulness of this parametrisation, a hierarchical model-based feedback controller is implemented. The controller is verified and evaluated in simulation on various dynamical tasks, where the nullspace motions, disturbance recovery, and trajectory tracking capabilities of the platform are examined and validated. The soft flying manipulator platform could open new application fields in aerial construction, goods delivery, human assistance, maintenance, and warehouse automation.
Modeling and Control of an Omnidirectional Micro Aerial Vehicle Equipped with a Soft Robotic Arm
Szász, Róbert; Allenspach, Mike; Han Minghao; et al. (2021)
arXiv
Flying manipulators are aerial drones with attached rigid-bodied robotic arms and belong to the latest and most actively developed research areas in robotics. The rigid nature of these arms often lack compliance, flexibility, and smoothness in movement. This work proposes to use a soft-bodied robotic arm attached to an omnidirectional micro aerial vehicle (OMAV) to leverage the compliant and flexible behavior of the arm, while remaining maneuverable and dynamic thanks to the omnidirectional drone as the floating base. The unification of the arm with the drone poses challenges in the modeling and control of such a combined platform; these challenges are addressed with this work. We propose a unified model for the flying manipulator based on three modeling principles: the Piecewise Constant Curvature (PCC) and Augmented Rigid Body Model (ARBM) hypotheses for modeling soft continuum robots and a floating-base approach borrowed from the traditional rigid-body robotics literature. To demonstrate the validity and usefulness of this parametrisation, a hierarchical model-based feedback controller is implemented. The controller is verified and evaluated in simulation on various dynamical tasks, where the nullspace motions, disturbance recovery, and trajectory tracking capabilities of the platform are examined and validated. The soft flying manipulator platform could open new application fields in aerial construction, goods delivery, human assistance, maintenance, and warehouse automation.
Mixed Reality Human-Robot Interface to Generate and Visualize 6DoF Trajectories: Application to Omnidirectional Aerial Vehicles
Allenspach, Mike; Laasch, Severin; Lawrance, Nicholas; et al. (2023)
2023 International Conference on Unmanned Aircraft Systems (ICUAS)
Omnidirectional aerial vehicles are an attractive tool for automated inspection tasks. Planning suitable trajectories in industrial environments is not trivial though and often requires human input. Existing trajectory planning tools generally rely on prior and accurate models of both the environment and the vehicle. Furthermore, their common 2D visualization for human operators is generally unsuitable for intuitive understanding of motions in SE(3). In this work, we exploit Mixed Reality to improve and simplify mission planning, by allowing the user to generate and perceive a trajectory directly in the real environment. The operator can precisely and intuitively plan a dynamically-feasible 6DoF trajectory by adding and modifying waypoints. Each waypoint is visualized as a holographic representation of the physical robot including the camera frustum for visual inspection tasks. Dynamic and static holograms corresponding to spatial and temporal information of the resulting trajectory are also overlaid onto the real world, allowing an operator to quickly assess potential collisions and inspection coverage. We experimentally demonstrate the effectiveness of the developed application and indicate its efficiency based on related work. The encouraging results motivate future quantitative evaluations in the form of user studies.

Publications 1 - 10 of 18

Mike Allenspach

Last Name

First Name

ORCID

Organisational unit

Filters

Search Results