Combining Sensors and Multibody Models for Applications in Vehicles, Machines, Robots and Humans

• Other Authors: Cuadrado, Javier (Editor), Naya, Miguel (Editor)
• Format: Electronic Book Chapter
• Language: English
• Published: Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute 2021
• Subjects: Technology: general issues; Kalman filter; motion capture; gait analysis; inertial sensor; rail vehicles; track irregularities; multibody dynamics; inertial sensors; computer vision; singular configuration; parallel robot; motion control; 3D tracking; screw theory; Kalman filtering; coupled states-inputs estimation; virtual sensors; slider-crank mechanism; virtual sensoring; physical sensors; smart/intelligent sensors; sensor technology and applications; sensing principles; signal processing in sensor systems; symbolic generation; real-time computation; human-in-the-loop; haptic devices; parameter estimation; curve fitting method; hydraulic system; predictive maintenance; characteristic curve; product life cycle; digital twin; adaptive Kalman filter; nonlinear models; virtual sensing; multibody based observers; vehicle dynamics estimation; sideslip angle estimation; factor graph; graphical models; movable repetitive lander; fault-tolerant soft-landing; landing configuration; stability optimization; n/a
• Online Access: DOAB: download the publication; DOAB: description of the publication

The combination of physical sensors and computational models to provide additional information about system states, inputs and/or parameters, in what is known as virtual sensing, is becoming increasingly popular in many sectors, such as the automotive, aeronautics, aerospatial, railway, machinery, r...