A featureless approach for object detection and tracking in dynamic environments

One of the challenging problems in mobile robotics is mapping a dynamic environment for navigating robots. In order to disambiguate multiple moving obstacles, state-of-art techniques often solve some form of dynamic SLAM (Simultaneous Localization and Mapping) problem. Unfortunately, their higher computational complexity press the need for simpler and more efficient approaches suitable for real-time embedded systems. In this paper, we present a ROS-based efficient algorithm for constructing dynamic maps, which exploits the spatial-temporal locality for detecting and tracking moving objects without relying on prior knowledge of their geometrical features. A two-prong contribution of this work is as follows: first, an efficient scheme for decoding sensory data into an estimated time-varying object boundary that ultimately decides its orientation and trajectory based on the iteratively updated robot Field of View (FoV); second, lower time-complexity of updating the dynamic environment through manipulating spatial-temporal locality available in the object motion profile. Unlike existing approaches, the snapshots of the environment remain constant in the number of moving objects. We validate the efficacy of our algorithm on both V-Rep simulations and real-life experiments with a wide array of dynamic environments. We show that the algorithm accurately detects and tracks objects with a high probability as long as sensor noise is low and the speed of moving objects remains within acceptable limits

Breathing new life into tissue engineering: exploring cutting-edge vascularization strategies for skin substitutes

Tissue-engineered skin substitutes (TESS) emerged as a new therapeutic option to improve skin transplantation. However, establishing an adequate and rapid vascularization in TESS is a critical factor for their clinical application and successful engraftment in patients. Therefore, several methods have been applied to improve the vascularization of skin substitutes including (i) modifying the structural and physicochemical properties of dermal scaffolds; (ii) activating biological scaffolds with growth factor-releasing systems or gene vectors; and (iii) developing prevascularized skin substitutes by loading scaffolds with capillary-forming cells. This review provides a detailed overview of the most recent and important developments in the vascularization strategies for skin substitutes. On the one hand, we present cell-based approaches using stem cells, microvascular fragments, adipose tissue derived stromal vascular fraction, endothelial cells derived from blood and skin as well as other pro-angiogenic stimulation methods. On the other hand, we discuss how distinct 3D bioprinting techniques and microfluidics, miRNA manipulation, cell sheet engineering and photosynthetic scaffolds like GelMA, can enhance skin vascularization for clinical applications. Finally, we summarize and discuss the challenges and prospects of the currently available vascularization techniques that may serve as a steppingstone to a mainstream application of skin tissue engineering

A Review on Text Detection Techniques

Text detection in image is an important field. Reading text is challenging because of the variations in images. Text detection is useful for many navigational purposes e.g. text on google API’s and traffic panels etc. This paper analyzes the work done on text detection by many researchers and critically evaluates the techniques designed for text detection and states the limitation of each approach. We have integrated the work of many researchers for getting a brief over view of multiple available techniques and their strengths and limitations are also discussed to give readers a clear picture. The major dataset discussed in all these papers are ICDAR 2003, 2005, 2011, 2013 and SVT(street view text).