A. Bredenbeck
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1
Aerial robots are widely employed for exploration, inspection, and environmental monitoring, where their agility and maneuverability are strong assets. However, their endurance remains limited, inhibiting their applicability in long-term missions. Perching, the ability to attach to environmental structures and rest with minimal power, offers a solution. Yet existing methods typically rely on bespoke attachment mechanisms tuned to a single, known, and predefined target, as well as vision-based target detection systems, prone to noise and occlusions, forcing reliance on brittle feed-forward control. We introduce a tactile-driven perching strategy for aerial robots that refines pose through touch. The system integrates a compliant anthropomorphic hand with embedded binary tactile sensors, enabling closed-loop alignment and grasp stability assessment through direct physical interaction. In simulation, the method achieves over 99% perching success across diverse geometries and pose errors up to 0.6 m and 50°. Hardware experiments validate robust perching across 26 real-world trials on diverse structures, despite corrupted pose estimates. By embedding tactile feedback into perching, this work advances a new paradigm, enabling micro aerial vehicles to exploit contact as informative feedback rather than relying solely on pre-contact visual estimates, facilitating robust autonomous perching on diverse, previously unseen targets in unstructured environments.
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Aerial robots are widely employed for exploration, inspection, and environmental monitoring, where their agility and maneuverability are strong assets. However, their endurance remains limited, inhibiting their applicability in long-term missions. Perching, the ability to attach to environmental structures and rest with minimal power, offers a solution. Yet existing methods typically rely on bespoke attachment mechanisms tuned to a single, known, and predefined target, as well as vision-based target detection systems, prone to noise and occlusions, forcing reliance on brittle feed-forward control. We introduce a tactile-driven perching strategy for aerial robots that refines pose through touch. The system integrates a compliant anthropomorphic hand with embedded binary tactile sensors, enabling closed-loop alignment and grasp stability assessment through direct physical interaction. In simulation, the method achieves over 99% perching success across diverse geometries and pose errors up to 0.6 m and 50°. Hardware experiments validate robust perching across 26 real-world trials on diverse structures, despite corrupted pose estimates. By embedding tactile feedback into perching, this work advances a new paradigm, enabling micro aerial vehicles to exploit contact as informative feedback rather than relying solely on pre-contact visual estimates, facilitating robust autonomous perching on diverse, previously unseen targets in unstructured environments.
Journal article
(2026)
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Jasper Zevering, Joshua Braun, Martin Hesse, Kedus Mathewos, Dorit Borrmann, Anton Bredenbeck, Andreas Nüchter
The exploration of lunar caves is a critical aspect of the space exploration program of the European Space Agency (ESA). To facilitate this mission, the DAEDALUS study investigated a novel spherical robot design in 2021. The proposed robot uses a unique telescopic linear rod mechanism to generate rotation and hence locomotion. This drive mechanism requires a dedicated control scheme to ensure both locomotion and simultaneously stabilization of the robot. The overall task of following a curved trajectory is also a problem that cannot be solved by simple algorithms. In this work, we introduce, calculate, and simulate a solution for these tasks, the Virtual Pose Instruction Plane (VPIP). The VPIP breaks the problem of multiple independent controllable rods down to two controllable parameters (roll and pitch of the plane), which control the linear motion velocity, balance and ultimately curvature motion of the robot. Initial simulations show that both speed and cornering can be controlled by the VPIP.
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The exploration of lunar caves is a critical aspect of the space exploration program of the European Space Agency (ESA). To facilitate this mission, the DAEDALUS study investigated a novel spherical robot design in 2021. The proposed robot uses a unique telescopic linear rod mechanism to generate rotation and hence locomotion. This drive mechanism requires a dedicated control scheme to ensure both locomotion and simultaneously stabilization of the robot. The overall task of following a curved trajectory is also a problem that cannot be solved by simple algorithms. In this work, we introduce, calculate, and simulate a solution for these tasks, the Virtual Pose Instruction Plane (VPIP). The VPIP breaks the problem of multiple independent controllable rods down to two controllable parameters (roll and pitch of the plane), which control the linear motion velocity, balance and ultimately curvature motion of the robot. Initial simulations show that both speed and cornering can be controlled by the VPIP.
Journal article
(2026)
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Dielof van Loon, Anton Bredenbeck, Lennart Puck, Martin Azkarate, Salua Hamaza
Recent developments in planetary exploration have shown the potential of Uncrewed Aerial Vehicles (UAVs), such as the Ingenuity helicopter that provided valuable mapping data. However, limited payload capabilities constrain the flight times and compute available for localization which restrict their applicability. By providing a tethered connection, issues such as battery and computational constraints are offloaded to the base rover. At the same time, the cable can be exploited for non-drifting localization. This work presents a novel Tether-Inertial Localization approach that uses tether length, and angle measurements to estimate the UAV position relative to its base. The method combines a computationally efficient analytical catenary model with a Gaussian Process (GP) residual error compensation. This accounts for systematic sensor inaccuracies and model limitations. Experimental validation across circular, triangular, and figure-eight trajectories with tether lengths up to 4.5 m and a total flight time of 37 minutes demonstrates the effectiveness of the proposed approach. Using only tether-based position estimates for feedback, the analytical catenary model achieves an average RMSE of 7.4 cm, which is further reduced to 5.2 cm through GP-based residual compensation, one order of magnitude better than the state-of-the-art. These results establish Tether-Inertial Localization as a practical alternative to vision- and GNSS-based localization for Tethered Uncrewed Aerial Vehicles (TUAVs).
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Recent developments in planetary exploration have shown the potential of Uncrewed Aerial Vehicles (UAVs), such as the Ingenuity helicopter that provided valuable mapping data. However, limited payload capabilities constrain the flight times and compute available for localization which restrict their applicability. By providing a tethered connection, issues such as battery and computational constraints are offloaded to the base rover. At the same time, the cable can be exploited for non-drifting localization. This work presents a novel Tether-Inertial Localization approach that uses tether length, and angle measurements to estimate the UAV position relative to its base. The method combines a computationally efficient analytical catenary model with a Gaussian Process (GP) residual error compensation. This accounts for systematic sensor inaccuracies and model limitations. Experimental validation across circular, triangular, and figure-eight trajectories with tether lengths up to 4.5 m and a total flight time of 37 minutes demonstrates the effectiveness of the proposed approach. Using only tether-based position estimates for feedback, the analytical catenary model achieves an average RMSE of 7.4 cm, which is further reduced to 5.2 cm through GP-based residual compensation, one order of magnitude better than the state-of-the-art. These results establish Tether-Inertial Localization as a practical alternative to vision- and GNSS-based localization for Tethered Uncrewed Aerial Vehicles (TUAVs).
Highlights: What are the main findings? The proposed approach exploits tactile feedback from collisions to infer obstacle locationsin the environment. Our collision-aware estimator uses pre-collision velocities, rates and tactile feedback topredict post-collision velocities and rates alongside a vector-field-based path representationand recovery strategy to improve state estimation and ensure safe traversal ofcluttered environments at low computational cost. What are the implications of the main findings? The proposed method enables robust navigation in environments where traditionalvision- or range-based sensing is unreliable. The proposed method allows drones to recover in-flight from high-speed collisions andadapt their paths afterwards, preventing repeated impacts and improving resilience incluttered settings. Aerial robots are a well-established solution for exploration, monitoring, and inspection, thanks to their superior maneuverability and agility. However, in many environments, they risk crashing and sustaining damage after collisions. Traditional methods focus on avoiding obstacles entirely, but these approaches can be limiting, particularly in cluttered spaces or on weight- and computationally constrained platforms such as drones. This paper presents a novel approach to enhance drone robustness and autonomy by developing a path recovery and adjustment method for a high-speed collision-resilient aerial robot equipped with lightweight, distributed tactile sensors. The proposed system explicitly models collisions using pre-collision velocities, rates and tactile feedback to predict post-collision dynamics, improving state estimation accuracy. Additionally, we introduce a computationally efficient vector-field-based path representation that guarantees convergence to a user-specified path, while naturally avoiding known obstacles. Post-collision, contact point locations are incorporated into the vector field as a repulsive potential, enabling the drone to avoid obstacles while naturally returning to its path. The effectiveness of this method is validated through Monte Carlo simulations and demonstrated on a physical prototype, showing successful path following, collision recovery, and adjustment at speeds up to (Formula presented.) (Formula presented.) / (Formula presented.).
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Highlights: What are the main findings? The proposed approach exploits tactile feedback from collisions to infer obstacle locationsin the environment. Our collision-aware estimator uses pre-collision velocities, rates and tactile feedback topredict post-collision velocities and rates alongside a vector-field-based path representationand recovery strategy to improve state estimation and ensure safe traversal ofcluttered environments at low computational cost. What are the implications of the main findings? The proposed method enables robust navigation in environments where traditionalvision- or range-based sensing is unreliable. The proposed method allows drones to recover in-flight from high-speed collisions andadapt their paths afterwards, preventing repeated impacts and improving resilience incluttered settings. Aerial robots are a well-established solution for exploration, monitoring, and inspection, thanks to their superior maneuverability and agility. However, in many environments, they risk crashing and sustaining damage after collisions. Traditional methods focus on avoiding obstacles entirely, but these approaches can be limiting, particularly in cluttered spaces or on weight- and computationally constrained platforms such as drones. This paper presents a novel approach to enhance drone robustness and autonomy by developing a path recovery and adjustment method for a high-speed collision-resilient aerial robot equipped with lightweight, distributed tactile sensors. The proposed system explicitly models collisions using pre-collision velocities, rates and tactile feedback to predict post-collision dynamics, improving state estimation accuracy. Additionally, we introduce a computationally efficient vector-field-based path representation that guarantees convergence to a user-specified path, while naturally avoiding known obstacles. Post-collision, contact point locations are incorporated into the vector field as a repulsive potential, enabling the drone to avoid obstacles while naturally returning to its path. The effectiveness of this method is validated through Monte Carlo simulations and demonstrated on a physical prototype, showing successful path following, collision recovery, and adjustment at speeds up to (Formula presented.) (Formula presented.) / (Formula presented.).
Conference paper
(2023)
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J.P. R Ramirez, A. Bredenbeck, S. Hamaza
Traditional landing gear consists of rigid linkages with dampers. They require a flat surface to function. In unstructured environments such as lunar craters or the martian polar region, these conditions are not always met. In this work, we equip a conventional quadrotor with four continuously deformable passive landing limbs with a logarithmic spiral geometry. By choosing the right geometric design as well as tension on the tendon running through the length of the limbs, we ensure that the limbs support the overall weight while passively complying to the environment. Hence, no active control during the landing process is needed in order to adapt to irregular ground. In a set of experiments, these compliant limbs showcase their ability to adjust to uneven landing terrain while maintaining the horizontal attitude of the base vehicle. Overall, this work highlights the future potential to access more challenging environments, leveraging physical compliance for robust landings.
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Traditional landing gear consists of rigid linkages with dampers. They require a flat surface to function. In unstructured environments such as lunar craters or the martian polar region, these conditions are not always met. In this work, we equip a conventional quadrotor with four continuously deformable passive landing limbs with a logarithmic spiral geometry. By choosing the right geometric design as well as tension on the tendon running through the length of the limbs, we ensure that the limbs support the overall weight while passively complying to the environment. Hence, no active control during the landing process is needed in order to adapt to irregular ground. In a set of experiments, these compliant limbs showcase their ability to adjust to uneven landing terrain while maintaining the horizontal attitude of the base vehicle. Overall, this work highlights the future potential to access more challenging environments, leveraging physical compliance for robust landings.
Conference paper
(2022)
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A. Bredenbeck, S. Vyas, Martin Zwick, Dorit Borrmann, Miguel Olivares-Mendez, Andreas Nüchter
The recent increase in yearly spacecraft launches and the high number of planned launches have raised questions about maintaining accessibility to space for all interested parties. A key to sustaining the future of space-flight is the ability to service malfunctioning - and actively remove dysfunctional spacecraft from orbit. Robotic platforms that autonomously perform these tasks are a topic of ongoing research and thus must undergo thorough testing before launch. For representative system-level testing, the European Space Agency (ESA) uses, among other things, the Orbital Robotics and GNC Lab (ORGL), a flat-floor facility where air-bearing based platforms exhibit free-floating behavior in three Degrees of Freedom (DoF). This work introduces a representative simulation of a free-floating platform in the testing environment and a software framework for controller development. Finally, this work proposes a controller within that framework for finding and following optimal trajectories between arbitrary states, which is evaluated in simulation and reality.
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The recent increase in yearly spacecraft launches and the high number of planned launches have raised questions about maintaining accessibility to space for all interested parties. A key to sustaining the future of space-flight is the ability to service malfunctioning - and actively remove dysfunctional spacecraft from orbit. Robotic platforms that autonomously perform these tasks are a topic of ongoing research and thus must undergo thorough testing before launch. For representative system-level testing, the European Space Agency (ESA) uses, among other things, the Orbital Robotics and GNC Lab (ORGL), a flat-floor facility where air-bearing based platforms exhibit free-floating behavior in three Degrees of Freedom (DoF). This work introduces a representative simulation of a free-floating platform in the testing environment and a software framework for controller development. Finally, this work proposes a controller within that framework for finding and following optimal trajectories between arbitrary states, which is evaluated in simulation and reality.
Unmanned Aerial Vehicles (UAVs) are widely used for environmental surveying and exploration thanks to their maneuverability and accessibility. Until recently, however, these platforms were mainly used as passive systems that observe their environments visually and do not interact physically. The capability of UAVs to physically interact with their environment, also known as Aerial Manipulators (AMs), allows them to do a wider variety of tasks. These tasks include contact inspection, manipulation of objects, and more. To successfully interact with the environment, the AM must compensate for the contact-induced disturbance forces. One approach is to estimate the contact force and compensate for it within the control approach. This work introduces a framework to estimate the contact force at the End-Effector (EE) using only state measurements of the generic AM. Further, the evaluation of the framework in a simulation of an AM with a tendon-driven robotic arm shows that it precisely estimates the contact force.
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Unmanned Aerial Vehicles (UAVs) are widely used for environmental surveying and exploration thanks to their maneuverability and accessibility. Until recently, however, these platforms were mainly used as passive systems that observe their environments visually and do not interact physically. The capability of UAVs to physically interact with their environment, also known as Aerial Manipulators (AMs), allows them to do a wider variety of tasks. These tasks include contact inspection, manipulation of objects, and more. To successfully interact with the environment, the AM must compensate for the contact-induced disturbance forces. One approach is to estimate the contact force and compensate for it within the control approach. This work introduces a framework to estimate the contact force at the End-Effector (EE) using only state measurements of the generic AM. Further, the evaluation of the framework in a simulation of an AM with a tendon-driven robotic arm shows that it precisely estimates the contact force.
Book chapter
(2022)
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Fabian Arzberger, Jasper Zevering, A. Bredenbeck, Dorit Borrmann, Andreas Nüchter
State-of-the-art LiDAR-based 3D scanning and mapping systems focus on scenarios where good sensing coverage is ensured, such as drones, wheeled robots, cars, or backpack-mounted systems. However, in some scenarios more unconventional sensor trajectories come naturally, e.g., rolling, descending, or oscillating back and forth, but the literature on these is relatively sparse. As a result, most implementations developed in the past are not able to solve the SLAM problem in such conditions. In this chapter, we propose a robust offline-batch SLAM system that is able to address more challenging trajectories, which are characterized by weak angles of incidence and limited FOV while scanning. The proposed SLAM system is an upgraded version of our previous work and takes as input the raw points and prior pose estimates, yet the latter are subject to large amounts of drift. Our approach is a two-staged algorithm where in the first stage coarse alignment is fast achieved by matching planar polygons. In the second stage, we utilize a graph-based SLAM algorithm for further refinement. We evaluate the mapping accuracy of the algorithm on our own recorded datasets using high-resolution ground truth maps, which are available from a TLS.
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State-of-the-art LiDAR-based 3D scanning and mapping systems focus on scenarios where good sensing coverage is ensured, such as drones, wheeled robots, cars, or backpack-mounted systems. However, in some scenarios more unconventional sensor trajectories come naturally, e.g., rolling, descending, or oscillating back and forth, but the literature on these is relatively sparse. As a result, most implementations developed in the past are not able to solve the SLAM problem in such conditions. In this chapter, we propose a robust offline-batch SLAM system that is able to address more challenging trajectories, which are characterized by weak angles of incidence and limited FOV while scanning. The proposed SLAM system is an upgraded version of our previous work and takes as input the raw points and prior pose estimates, yet the latter are subject to large amounts of drift. Our approach is a two-staged algorithm where in the first stage coarse alignment is fast achieved by matching planar polygons. In the second stage, we utilize a graph-based SLAM algorithm for further refinement. We evaluate the mapping accuracy of the algorithm on our own recorded datasets using high-resolution ground truth maps, which are available from a TLS.
Conference paper
(2021)
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Jasper Zevering, A. Bredenbeck, Fabian Arzberger, Dorit Borrmann, Andreas Nüchter
Spherical robots are a robot format that is not yet thoroughly studied for the application of mobile mapping. However, in contrast to other forms, they provide some unique advantages. For one, the spherical shell provides protection against harsh environments, e.g., guarding the sensors and actuators against dust and solid rock. This is particularly useful in space applications. Furthermore, the inherent rotation the robot uses for locomotion can be exploited to measure in all directions without having the sensor itself actuated. A reasonable estimation of the robot pose is required to exploit this rotation in combination with sensor data to create a consistent environment map. This raises the need for interpolating instances for calculation-intensive slow algorithms such as optical localization algorithms or as an initial estimate for subsequent simultaneous localization and mapping (SLAM). In such cases, inertial measurements from sensors such as accelerometers and gyroscopes generate a pose estimate for these interpolation steps. The paper presents a pose estimation procedure based on inertial measurements, that exploits the known dynamics of a spherical robot. It emphasizes a low jitter to maintain constant world measurements during standstill and avoids exponentially growing error in position estimates. Evaluating the position and orientation estimates with given ground truth frames shows that we reduce the jitter in orientation and handle slip and partly slide behavior better than other commonly used filters such as the Madgwick filter.
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Spherical robots are a robot format that is not yet thoroughly studied for the application of mobile mapping. However, in contrast to other forms, they provide some unique advantages. For one, the spherical shell provides protection against harsh environments, e.g., guarding the sensors and actuators against dust and solid rock. This is particularly useful in space applications. Furthermore, the inherent rotation the robot uses for locomotion can be exploited to measure in all directions without having the sensor itself actuated. A reasonable estimation of the robot pose is required to exploit this rotation in combination with sensor data to create a consistent environment map. This raises the need for interpolating instances for calculation-intensive slow algorithms such as optical localization algorithms or as an initial estimate for subsequent simultaneous localization and mapping (SLAM). In such cases, inertial measurements from sensors such as accelerometers and gyroscopes generate a pose estimate for these interpolation steps. The paper presents a pose estimation procedure based on inertial measurements, that exploits the known dynamics of a spherical robot. It emphasizes a low jitter to maintain constant world measurements during standstill and avoids exponentially growing error in position estimates. Evaluating the position and orientation estimates with given ground truth frames shows that we reduce the jitter in orientation and handle slip and partly slide behavior better than other commonly used filters such as the Madgwick filter.
Conference paper
(2021)
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Dorit Borrmann, Andreas Nüchter, A. Bredenbeck, Jasper Zevering, Fabian Arzberger, Camillo Andres Reyes Mantilla, Angelo Pio Rossi, Francesco Maurelli, Vikram Unnithan, More authors...
The DAEDALUS mission design concept aims at exploring and characterising the entrance of lunar lava tubes within a compact, tightly integrated spherical robotic device, with a complementary payload set and autonomous capabilities.
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The DAEDALUS mission design concept aims at exploring and characterising the entrance of lunar lava tubes within a compact, tightly integrated spherical robotic device, with a complementary payload set and autonomous capabilities.
Report
(2021)
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Angelo Pio Rossi, Francesco Maurelli, Vikram Unnithan, Hendrik Dreger, Kedus Mathewos, Nayan Pradhan, Dan-Andrei Corbeanu, Riccardo Pozzobon, A. Bredenbeck, More authors...
The DAEDALUS mission concept aims at exploring and characterising the entrance and initial part of Lunar lava tubes within a compact, tightly integrated spherical robotic device, with a complementary payload set and autonomous capabilities. The mission concept addresses specifically the identification and characterisation of potential resources for future ESA exploration, the local environment of the subsurface and its geologic and compositional structure. A sphere is ideally suited to protect sensors and scientific equipment in rough, uneven environments. It will house laser scanners, cameras and ancillary payloads. The sphere will be lowered into the skylight and will explore the entrance shaft, associated caverns and conduits. Lidar (light detection and ranging) systems produce 3D models with high spatial accuracy independent of lighting conditions and visible features. Hence this will be the primary exploration toolset within the sphere. The additional payload that can be accommodated in the robotic sphere consists of camera systems with panoramic lenses and scanners such as multi-wavelength or single-photon scanners. A moving mass will trigger movements. The tether for lowering the sphere will be used for data communication and powering the equipment during the descending phase. Furthermore, the connector tether-sphere will host a WIFI access point, such that data of the conduit can be transferred to the surface relay station. During the exploration phase, the robot will be disconnected from the cable, and will use wireless communication. Emergency autonomy software will ensure that in case of loss of communication, the robot will continue the nominal mission.
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The DAEDALUS mission concept aims at exploring and characterising the entrance and initial part of Lunar lava tubes within a compact, tightly integrated spherical robotic device, with a complementary payload set and autonomous capabilities. The mission concept addresses specifically the identification and characterisation of potential resources for future ESA exploration, the local environment of the subsurface and its geologic and compositional structure. A sphere is ideally suited to protect sensors and scientific equipment in rough, uneven environments. It will house laser scanners, cameras and ancillary payloads. The sphere will be lowered into the skylight and will explore the entrance shaft, associated caverns and conduits. Lidar (light detection and ranging) systems produce 3D models with high spatial accuracy independent of lighting conditions and visible features. Hence this will be the primary exploration toolset within the sphere. The additional payload that can be accommodated in the robotic sphere consists of camera systems with panoramic lenses and scanners such as multi-wavelength or single-photon scanners. A moving mass will trigger movements. The tether for lowering the sphere will be used for data communication and powering the equipment during the descending phase. Furthermore, the connector tether-sphere will host a WIFI access point, such that data of the conduit can be transferred to the surface relay station. During the exploration phase, the robot will be disconnected from the cable, and will use wireless communication. Emergency autonomy software will ensure that in case of loss of communication, the robot will continue the nominal mission.
Journal article
(2021)
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Fabian Arzberger, A. Bredenbeck, Jasper Zevering, Dorit Borrmann, Andreas Nüchter
Spherical robots are a format that has not been thoroughly explored for the application of mobile mapping. In contrast to other designs, it provides some unique advantages. Among those is a spherical shell that protects internal sensors and actuators from possible harsh environments, as well as an inherent rotation for locomotion that enables measurements in all directions. Mobile mapping always requires a high-precise pose knowledge to obtain consistent and correct environment maps. This is typically done by a combination of external reference sensors such as Global Navigation Satellite System (GNSS) measurements and inertial measurements or by coarsely estimating the pose using inertial measurement units (IMUs) and post processing the data by registering the different measurements to each other. In indoor environments, the GNSS reference is not an option. Hence many mobile mapping applications turn to the second option. An advantage of indoor environments is that human-made environments usually have a certain structure, such as parallel and perpendicular planes. We propose a registration procedure that exploits this structure by minimizing the distance of measured points to a corresponding plane. Further, we evaluate the procedure on a simulated dataset of an ideal corridor and on an experimentally acquired dataset with different motion profiles. We show that we nearly reproduce the ground truth for the simulated dataset and improve the average point-to-point distance to a reference scan in the experimental dataset. The presented algorithms are required to work completely autonomously.
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Spherical robots are a format that has not been thoroughly explored for the application of mobile mapping. In contrast to other designs, it provides some unique advantages. Among those is a spherical shell that protects internal sensors and actuators from possible harsh environments, as well as an inherent rotation for locomotion that enables measurements in all directions. Mobile mapping always requires a high-precise pose knowledge to obtain consistent and correct environment maps. This is typically done by a combination of external reference sensors such as Global Navigation Satellite System (GNSS) measurements and inertial measurements or by coarsely estimating the pose using inertial measurement units (IMUs) and post processing the data by registering the different measurements to each other. In indoor environments, the GNSS reference is not an option. Hence many mobile mapping applications turn to the second option. An advantage of indoor environments is that human-made environments usually have a certain structure, such as parallel and perpendicular planes. We propose a registration procedure that exploits this structure by minimizing the distance of measured points to a corresponding plane. Further, we evaluate the procedure on a simulated dataset of an ideal corridor and on an experimentally acquired dataset with different motion profiles. We show that we nearly reproduce the ground truth for the simulated dataset and improve the average point-to-point distance to a reference scan in the experimental dataset. The presented algorithms are required to work completely autonomously.
Conference paper
(2020)
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Jasper Zevering, A. Bredenbeck, Fabian Arzberger, Dorit Borrmann, Andreas Nüchter
This paper proposes an autonomous approach to 3D mapping using the concept of impulse by conservation of angular momentum (IBCOAM) as a unidirectional drive to roll a 2D laser scanner in an IMU equipped, pose-tracked spherical robot system. An experimental prototype of the robot is introduced, giving details about the hardware. The laser scanning results as well as the IBCOAM drive data that have been gathered using the prototype are analyzed, revealing technical challenges.
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This paper proposes an autonomous approach to 3D mapping using the concept of impulse by conservation of angular momentum (IBCOAM) as a unidirectional drive to roll a 2D laser scanner in an IMU equipped, pose-tracked spherical robot system. An experimental prototype of the robot is introduced, giving details about the hardware. The laser scanning results as well as the IBCOAM drive data that have been gathered using the prototype are analyzed, revealing technical challenges.
Conference paper
(2020)
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Sergey Nikolskiy, A. Bredenbeck, Topi Rikkinen, M.C. Koivisto, Salomon Honkala, Zahidul Bhuiyan, Sarang Thombre
This paper analyzed the feasibility of development of a GNSS signal quality monitoring system that utilizes observation data provided by a reference station network. We present an overview of possible data sources and analysis techniques that can be used. The details about the software prototype developed are provided. Finally, we elaborate on the system scalability and the steps to extend the capabilities.
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This paper analyzed the feasibility of development of a GNSS signal quality monitoring system that utilizes observation data provided by a reference station network. We present an overview of possible data sources and analysis techniques that can be used. The details about the software prototype developed are provided. Finally, we elaborate on the system scalability and the steps to extend the capabilities.