Vision-Based Autonomous Robotic Floor Cleaning in Domestic Environments

Fleer DR. Vision-Based Autonomous Robotic Floor Cleaning in Domestic Environments. Bielefeld: Universität Bielefeld; 2018

Visual tilt estimation for planar-motion methods in indoor mobile robots

Fleer DR. Visual tilt estimation for planar-motion methods in indoor mobile robots. Robotics. 2017;6(4): 32.Visual methods have many applications in mobile robotics problems, such as localization, navigation, and mapping. Some methods require that the robot moves in a plane without tilting. This planar-motion assumption simplifies the problem, and can lead to improved results. However, tilting the robot violates this assumption, and may cause planar-motion methods to fail. Such a tilt should therefore be corrected. In this work, we estimate a robot’s tilt relative to a ground plane from individual panoramic images. This estimate is based on the vanishing point of vertical elements, which commonly occur in indoor environments. We test the quality of two methods on images from several environments: An image-space method exploits several approximations to detect the vanishing point in a panoramic fisheye image. The vector-consensus method uses a calibrated camera model to solve the tilt-estimation problem in 3D space. In addition, we measure the time required on desktop and embedded systems. We previously studied visual pose-estimation for a domestic robot, including the effect of tilts. We use these earlier results to establish meaningful standards for the estimation error and time. Overall, we find the methods to be accurate and fast enough for real-time use on embedded systems. However, the tilt-estimation error increases markedly in environments containing relatively few vertical edges

Human-Like room segmentation for domestic cleaning robots

Fleer DR. Human-Like room segmentation for domestic cleaning robots. Robotics. 2017;6(4): 35.Autonomous mobile robots have recently become a popular solution for automating cleaning tasks. In one application, the robot cleans a floor space by traversing and covering it completely. While fulfilling its task, such a robot may create a map of its surroundings. For domestic indoor environments, these maps often consist of rooms connected by passageways. Segmenting the map into these rooms has several uses, such as hierarchical planning of cleaning runs by the robot, or the definition of cleaning plans by the user. Especially in the latter application, the robot-generated room segmentation should match the human understanding of rooms. Here, we present a novel method that solves this problem for the graph of a topo-metric map: first, a classifier identifies those graph edges that cross a border between rooms. This classifier utilizes data from multiple robot sensors, such as obstacle measurements and camera images. Next, we attempt to segment the map at these room–border edges using graph clustering. By training the classifier on user-annotated data, this produces a human-like room segmentation. We optimize and test our method on numerous realistic maps generated by our cleaning-robot prototype and its simulated version. Overall, we find that our method produces more human-like room segmentations compared to mere graph clustering. However, unusual room borders that differ from the training data remain a challen

Steuerung von Umgebungsintelligenz mit multimodalen Gesten

Fleer DR. Steuerung von Umgebungsintelligenz mit multimodalen Gesten. Bielefeld: Universität Bielefeld; 2011.I present an unobtrusive multimodal interface for smart objects (MISO) in an everyday indoor environment. MISO uses pointing for object selection and context-sensitive arm gestures for object control. Finger snaps are used to confirm object selections and to aid with gesture segmentation. Audio feedback is provided during the interaction. The use of a Kinect depth camera allows for a compact system and robustness in varying environments and lighting conditions at low cost

Comparing holistic and feature-based visual methods for estimating the relative pose of mobile robots

Fleer DR, Möller R. Comparing holistic and feature-based visual methods for estimating the relative pose of mobile robots. Robotics and Autonomous Systems. 2017;89:51-74

Cleaning robot navigation using panoramic views and particle clouds as landmarks

Möller R, Krzykawski M, Gerstmayr-Hillen L, Horst M, Fleer DR, de Jong J. Cleaning robot navigation using panoramic views and particle clouds as landmarks. Robotics and Autonomous Systems. 2013;61(12):1415-1439

Reattachment of the flexor and extensor tendons at the epicondyle in elbow instability: a biomechanical comparison of techniques

Abstract Background Elbow dislocation represents a common injury, especially in the younger population. If treated surgically, the reattached tendons require a high amount of primary stability to allow for an early rehabilitation to avoid postoperative stiffness. The purpose of this study was to assess the biomechanical properties of a single and a double row technique for reattachment of the common extensor and common flexor muscles origin. We hypothesized that the double row technique would provide greater stability in terms of pullout forces than the single row technique. Methods Twelve cadaveric specimens were randomized into two groups of fixation methods for the common extensor tendon or the common flexor tendon at the elbow (1): a single row technique using two knotted 3.0 mm suture anchors, and (2) a double row technique using an additional knotless 3.5 mm anchor. The repairs were cyclically loaded over 500 cycles at 1 Hz from 10 N to a maximum of 100 N (extensors) or 150 N (flexors), and then pulled to failure. Stiffness and maximum load at failure and mode of failure were recorded and calculated. Results No significant differences in stiffness were observed between the two techniques for both the extensor and flexor reattachment (P = 0.701 and P = 0.306, respectively). The mean maximum load at failure indicated that the double row construct was significantly stronger than the single row construct. This was found to be true for both the extensor and flexor reattachment (213.6; SD 78.7 N versus 384.1; SD 105.6 N, P = 0.010 and 203.7; SD 65.8 N versus 318.0; SD 64.6 N, P = 0.013, respectively). Conclusions The double row technique provides significant greater stability to the reattached common flexor or extensor origin to the medial or lateral epicondyle. Thus, it should be considered in the development of improved repair techniques for stabilizers of the elbow. Study design Controlled laboratory study