Filtern
Erscheinungsjahr
Dokumenttyp
Sprache
- Englisch (51) (entfernen)
Schlagworte
- Robotik (8)
- Flugkörper (7)
- UAV (7)
- Rettungsrobotik (5)
- Erweiterte Realität <Informatik> (3)
- Augmented Reality (2)
- Human-Robot Interaction (2)
- Twitter <Softwareplattform> (2)
- 360° Panorama (1)
- Alternative Geschäftsmodelle (1)
Institut
- Informatik und Kommunikation (51) (entfernen)
360° Camera at a small UAV
(2021)
Autonomy and self-determination are fundamental aspects of living in our society. Supporting people for whom this freedom is limited due to physical impairments is the fundamental goal of this thesis. Especially for people who are paralyzed, even working at a desk job is often not feasible. Therefore, in this thesis a prototype of a robot assembly workstation was constructed that utilizes a modern Augmented Reality (AR)-Head-Mounted Display (HMD) to control a robotic arm. Through the use of object pose recognition, the objects in the working environment are detected and this information is used to display different visual cues at the robotic arm or in its vicinity. Providing the users with additional depth information and helping them determine object relations, which are often not easily discernible from a fixed perspective.
To achieve this a hands-free AR-based robot-control scheme was developed, which uses speech and head-movement for interaction. Additionally, multiple advanced visual cues were designed that utilize object pose detection for spatial-visual support. The pose recognition system is adapted from state-of-the-art research in computer vision to allow the detection of arbitrary objects with no regard for texture or shape.
Two evaluations were performed, a small user study that excluded the object recognition, which confirms the general usability of the system and gives an impression on its performance. The participants were able to perform difficult pick and place tasks with a high success rate. Secondly, a technical evaluation of the object recognition system was conducted, which revealed an adequate prediction precision, but is too unreliable for real-world scenarios as the prediction quality is highly variable and depends on object orientations and occlusion.
Challenging visual localization of an UAV while flying out of a room into a snowy environment (~ 4:50). The UAV is equipped with a 360° camera. The localization is done with OpenVSLAM.
The video was recorded in Jan. 2019 at the Fire Brigade training center in Dortmund
To achieve nearly real time conditions the original resolution of 5k (30 fps) was reduced to 2k (ffmpeg -i video.mp4 -vf scale=1920:-1 -crf 25 vido-small.mp4) with high compression (-crf 25). This reduce the original size from 3.2 GB to 93MB (~ 4 MBit/s which could be transmitted online via a radio link). The localization shown did not use frameskip. With a frameskip above 1 the localization fails while the UAV is flying through the window. Indoor localization can be done with a frameskip of 3 in real time.
The article highlights gender codes in design, particularly in web design, by means of current examples. Different aspects of gender-specific design are looked at in detail and their inherent problems discussed: on the one hand the development of a special solution (gender-specific for women), on the other hand, web design with reduced functionality and simplification of information (i.e. image representation) which sometimes even leads to a negation of technology. The article illustrates that gender codes and stereotypical role models can be embodied on different design levels of web design (use and artefact): in structure/navigation, in creative elements by the use of shape, colour and imagery and on a textual level. These design decisions have an impact on the power of users to act, their individual gender identity and the structural gender identity/social perception of gender. The article demonstrates that gender codes in current web design are very present and aims to sensitize the topic.
This technical report is about the architecture and integration of commercial UAVs in Search and Rescue missions. We describe a framework that consists of heterogeneous UAVs, a UAV task planner, a bridge to the UAVs, an intelligent image hub, and a 3D point cloud generator. A first version of the framework was developed and tested in several training missions in the EU project TRADR.
Venice 2018: Tradr Review
(2018)
The video shows an orthopoto and a textured 3D model of the location. 300 images were recorded in two short flights with a Mavic Pro in 50 meter height. The first one was a single grid while the camera facing down and the second one was a double grid facing the camera at an 60 degree angle. The 3D model is computed with OpenDroneMap.
Opportunities and Challenges in Mixed-Reality for an Inclusive Human-Robot Collaboration Environment
(2018)
This paper presents an approach to enhance robot control using Mixed-Reality. It highlights the opportunities and challenges in the interaction design to achieve a Human-Robot Collaborative environment. In fact, Human-Robot Collaboration is the perfect space for social inclusion. It enables people, who suffer severe physical impairments, to interact with the environment by providing them movement control of an external robotic arm. Now, when discussing about robot control it is important to reduce the visual-split that different input and output modalities carry. Therefore, Mixed-Reality is of particular interest when trying to ease communication between humans and robotic systems.
A Robust Interface for Head Motion based Control of a Robot Arm using MARG and Visual Sensors
(2018)
Head-controlled human machine interfaces have gained popularity over the past years, especially in the restoration of the autonomy of severely disabled people, like tetraplegics. These interfaces need to be reliable and robust regarding the environmental conditions to guarantee safety of the user and enable a direct interaction between a human and a machine. This paper presents a hybrid MARG and visual sensor system for head orientation estimation which is in this case used to teleoperate a robotic arm. The system contains a Magnetic Angular Rate Gravity (MARG)-sensor and a Tobii eye tracker 4C. A MARG sensor consists of tri-axis accelerometer, gyroscope as well as a magnetometer which enable a complete measurement of orientation relative to the direction of gravity and magnetic field of the earth. The tri-axis magnetometer is sensitive to external magnetic fields which result in incorrect orientation estimation from the sensor fusion process. In this work the Tobii eye tracker 4C is used to increase head orientation estimation because it also features head tracking even though it is commonly used for eye tracking. This type of visual sensor does not suffer magnetic drift. However, it computes orientation data only, if a user is detectable. Within this work a state machine is presented which enables data fusion of the MARG and visual sensor to improve orientation estimation. The fusion of the orientation data of MARG and visual sensors enables a robust interface, which is immune against external magnetic fields. Therefore, it increases the safety of the human machine interaction.
Renewable and sustainable energy production by many small and distributed producers is revolutionizing the energy landscape as we know it. Consumers produce energy, making them to prosumers in the smart grid. The interaction between prosumers and other entities in the grid and the optimal utilization of new smart grid components (electric cars, freezers, solar panels, etc.) are crucial for the success of the smart grid. The Power Trading Agent Competition is an open simulation platform that allows researchers to conduct low risk studies in this new energy market. In this work we present Maxon16, an autonomous energy broker and champion of the 2016's Power Trading Agent Competition. We present the strategies the broker used in the final round and evaluate the effectiveness of the strategies by analyzing the tournament's results.
Global registration of heterogeneous ground and aerial mapping data is a challenging task. This is especially difficult in disaster response scenarios when we have no prior information on the environment and cannot assume the regular order of man-made environments or meaningful semantic cues. In this work we extensively evaluate different approaches to globally register UGV generated 3D point-cloud data from LiDAR sensors with UAV generated point-cloud maps from vision sensors. The approaches are realizations of different selections for: a) local features: key-points or segments; b) descriptors: FPFH, SHOT, or ESF; and c) transformation estimations: RANSAC or FGR. Additionally, we compare the results against standard approaches like applying ICP after a good prior transformation has been given. The evaluation criteria include the distance which a UGV needs to travel to successfully localize, the registration error, and the computational cost. In this context, we report our findings on effectively performing the task on two new Search and Rescue datasets. Our results have the potential to help the community take informed decisions when registering point-cloud maps from ground robots to those from aerial robots.
This paper presents a novel approach to build consistent 3D maps for multi robot cooperation in USAR environments. The sensor streams from unmanned aerial vehicles (UAVs) and ground robots (UGV) are fused in one consistent map. The UAV camera data are used to generate 3D point clouds that are fused with the 3D point clouds generated by a rolling 2D laser scanner at the UGV. The registration method is based on the matching of corresponding planar segments that are extracted from the point clouds. Based on the registration, an approach for a globally optimized localization is presented. Apart from the structural information of the point clouds, it is important to mention that no further information is required for the localization. Two examples show the performance of the overall registration.
The two churches, San Francesco and Sant'Agostino in Amatrice, Italy was hit by an earthquake on August 24 2016. Both churches are in a state of partial collapse, in need of shoring to prevent potential further destruction and to preserve the national heritage. The video show the mission at 1.Sept.2016 in clips of 10 seconds.
The TRADR project was asked by the Italian firebrigade Vigili del Fuoco to provide 3D textured models of two churches.
The team entered San Francesco with two UGVs (ground robots) and one UAV (drone, flown by Prof. Surmann), teleoperating them entirely out of line of sight and partially in collaboration. We entered Sant'Agostino with one UAV (also flown by Prof. Surmann) while two other UAVs were providing a view from different angles to facilitate maneuvering them entirely out of line of sight.