There are many outdoor robotic applications where a robot must reach a goal position or explore an area without previous knowledge of the environment around it. Additionally, other applications (like path planning) require the use of known maps or previous information of the environment. This work presents a system composed by a terrestrial and an aerial robot that cooperate and share sensor information in order to address those requirements. The ground robot is able to navigate in an unknown large environment aided by visual feedback from a camera on board the aerial robot. At the same time, the obstacles are mapped in real-time by putting together the information from the camera and the positioning system of the ground robot. A set of experiments were carried out with the purpose of verifying the system applicability. The experiments were performed in a simulation environment and outdoor with a medium-sized ground robot and a mini quad-rotor. The proposed robotic system shows outstanding results in simultaneous navigation and mapping applications in large outdoor environments.
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http://dx.doi.org/10.3390/s130101247 | DOI Listing |
J Comput Chem
January 2025
Scuola Superiore Meridionale, Napoli, Italy.
Light-driven molecular rotary motors are nanometric machines able to convert light into unidirectional motions. Several types of molecular motors have been developed to better respond to light stimuli, opening new avenues for developing smart materials ranging from nanomedicine to robotics. They have great importance in the scientific research across various disciplines, but a detailed comprehension of the underlying ultrafast photophysics immediately after photo-excitation, that is, Franck-Condon region characterization, is not fully achieved yet.
View Article and Find Full Text PDFInt J Radiat Oncol Biol Phys
January 2025
Department of Radiotherapy, University Medical Center Utrecht, Utrecht, The Netherlands.
Purpose: Deep learning is a promising approach to increase reproducibility and time-efficiency of GTV delineation in head and neck cancer, but model evaluation primarily relies on manual GTV delineations as reference annotation, which are subjective and tend to overestimate tumor volume. This study aimed to validate a deep learning model for laryngeal and hypopharyngeal GTV segmentation with pathology and to compare its performance with clinicians' manual delineations.
Materials And Methods: A retrospective dataset of 193 laryngeal and hypopharyngeal cancer patients was used to train a deep learning model with clinical GTV delineations as reference.
Rep U S
October 2024
Department of Mechanical Engineering, Johns Hopkins University, Baltimore, MD, USA.
In diagnosing and treating prostate cancer the flexible bevel tip needle insertion surgical technique is commonly used. Bevel tip needles experience asymmetric loading on the needle's tip, inducing natural bending of the needle and enabling control mechanisms for precise placement of the needle during surgery. Several methods leverage the needles natural bending to provide autonomous control of needle insertion for accurate needle placement in an effort to reduce excess tissue damage and improve patient outcomes from needle insertion intraventions.
View Article and Find Full Text PDFPhilos Trans R Soc Lond B Biol Sci
January 2025
Georgina Mace Centre for the Living Planet, Imperial College London, Silwood Park Campus, Ascot SL5 7PY, UK.
Africa boasts high biodiversity while also being home to some of the largest and fastest-growing human populations. Although the current environmental footprint of Africa is low compared to other continents, the population of Africa is estimated at around 1.5 billion inhabitants, representing nearly 18% of the world's total population.
View Article and Find Full Text PDFPatterns (N Y)
December 2024
Medical Robot Research Institute, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China.
This study developed an artificial intelligence (AI) system using a local-global multimodal fusion graph neural network (LGMF-GNN) to address the challenge of diagnosing major depressive disorder (MDD), a complex disease influenced by social, psychological, and biological factors. Utilizing functional MRI, structural MRI, and electronic health records, the system offers an objective diagnostic method by integrating individual brain regions and population data. Tested across cohorts from China, Japan, and Russia with 1,182 healthy controls and 1,260 MDD patients from 24 institutions, it achieved a classification accuracy of 78.
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