In this paper, we present a fully original control architecture for legged-and-climber robots that is level-based, hierarchical, and centralized. The architecture gives the robots the ability to perform self-reconfiguration after unforeseen leg failures, because it can control this kind of robot with different numbers of legs. The results show the capability of performing movements in any direction and inclination planes. The components and functionalities of the developed control architecture for these robots are described, and, the architecture’s performance is tested on the ROMHEX robot.
Background subtraction is one of the key pre-processing steps necessary for obtaining relevant information from a video sequence. The selection of a background subtraction algorithm and its parameters is also important for achieving optimal detection performance, especially in night environments. The research contribution presented in this paper is the identification of the optimal background subtractor algorithm in indoor night-time environments, with a focus on the detection of human falls. 30 background subtraction algorithms are analyzed to determine which has the best performance in indoor night-time environments. Genetic algorithms have been applied to identify the best background subtraction algorithm, to optimize the background subtractor parameters and to calculate the optimal number of pre-and post-processing operations. The results show that the best algorithm for fall-detection in indoor, night-time environments is the LBAdaptativeSOM, optimal parameters and processing operations for this algorithm are reported. INDEX TERMSFall detection, camera-based, background-subtraction. III. REVIEW OF THE BACKGROUND-SUBTRACTION ALGORITHMS UNDER ANALYSIS ALBERTO BRUNETE received the M.S. degree in telecommunication engineering and the Ph.D. degree in robotics and automation from the Universidad Politécnica de Madrid (UPM), in 2000 and 2010, respectively. He was the Technical Manager of the Research Center for Smart Buildings and Energy Efficiency (CeDInt), UPM, and a Visiting Professor with Carlos III University. He is currently an Associate Professor with the UPM and a Researcher with the Centre for Automation and Robotics, UPM. His main research interests include service robots and smart environments. In 2016, he has received the Spanish prize ABC Solidario of a fall detector project for elderly people. MIGUEL HERNANDO received the M.S. degree in electrical engineering degree and the Ph.D. degree in automatic control and robotics from the Universidad Politécnica de Madrid (UPM), in 1997 and 2003, respectively. He has participated in several international and national research and development projects on robotics. He is one of the founders of the startup Biicode whose aim is to give (C/C++) to a dependency manager (currently Conan.io). He is currently a Professor with the Department of Electronics and Automatic Control, UPM, where he is currently a Researcher with the Centre for Automation and Robotics (CAR), CSIC. His research interests include motion path planning, service robots, and micro-robotics. ERNESTO GAMBAO received the M.S. degree in electrical engineering and the Ph.D. degree in automatic control and robotics from the Universidad Politécnica de Madrid (UPM), Madrid, Spain, in 1996. He is currently a Professor with the Department of Automatic Control (UPM), where he is also a Researcher with the Centre for Automation and Robotics (CAR), CSIC.He has participated and coordinated numerous national and international research and development projects on robotics and automation. His research interests inclu...
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