Management of bone defects with Bio-oss

Introduction: The defects in the alveolar bone might appear as a result of congenital malformations, traumatic injuries, periodontal disease, surgical traumas, chronic periapical changes and tumors from benign or malignant origin. The aim of this study was to provide solid and healthy area with application of Bio-Oss in the defect. Materials and methods: Based on the clinical diagnosisestablished by previously taken history, clinical examination and radiographic images oral-surgery interventions was made. To realize the aim of this work, augmentative material was implicated in the bone defects made in the patients after removal of follicular cyst, chronic periapical lesion, and parodontopathia. During the first and seventh day of the interventions, the patients have been followed through from aspect of possible development of local and general complications after the oral-surgery intervention. After period of one, three and six mount control x-ray was made. Results: Obtained results confirmed that: volume of the socket and defect of the bone was kept, fast revascularization was achieved, bone formation and slow resorption of the augmentative material was achieved, and period of normal healing without infection was also achieved. Conclusions: The augmentative materials used for treatment of bone defects besides their basic chemical and physical characteristics referring to their solubility in the body fluids, the transformation, modulation and resorption must be completely safe or secure, i.e. not to bring any risk of infection, immunological risk, physiological intolerance or inhibition of the process of restitutio ad integrum. In our study Bio-Oss was confirmed as augmentative material who had this characteristics. Keywords: bone defect, resorption of the bone, augmentative material, Bio-Os

Object Detection and Tracking in Cooperative Multi-Robot Transportation

Contemporary manufacturing systems imply the utilization of autonomous robotic systems, mainly for the execution of manipulation and transportation tasks. With a goal to reduce transportation and manipulation time, improve efficiency, and achieve flexibility of intelligent manufacturing systems, two or more intelligent mobile robots can be exploited. Such multi-robot systems require coordination and some level of communication between heterogeneous or homogeneous robotic systems. In this paper, we propose the utilization of two heterogeneous robotic systems, original intelligent mobile robots RAICO (Robot with Artificial Intelligence based COgnition) and DOMINO (Deep learning-based Omnidirectional Mobile robot with Intelligent cOntrol), for transportation tasks within a laboratory model of a manufacturing environment. In order to reach an adequate cooperation level and avoid collision while moving along predefined paths, our own developed intelligent mobile robots RAICO and DOMINO will communicate their current poses, and object detection and tracking system is developed. A stereo vision system equipped with two parallelly placed industrial-grade cameras is used for image acquisition, while convolutional neural networks are utilized for object detection, classification, and tracking. The proposed object detection and tracking system enables real-time tracking of another mobile robot within the same manufacturing environment. Furthermore, continuous information about mobile robot poses and the size of the bounding box generated by the convolutional neural network in the process of detection of another mobile robot is used for estimation of object movement and collision avoidance. Mobile robot localization through time is performed based on kinematic models of two intelligent mobile robots, and conducted experiments within a laboratory model of manufacturing environment confirm the applicability of the proposed framework for object detection and collision avoidance