Research interests: E.J. Bayro-Corrochano

MS. degree in electronics and telecommunications gave me a very profound and pragmatic background of engineering. 
As postgraduate visitor in TH Aachen I became acquainted with digital signal processing, filtering and stochastic 
control engineering. During my PhD at the University of Wales College Cardiff I worked mainly on the development 
of algorithms for intelligent machine vision involving neural networks, image processing and pattern recognition. 
My PhD thesis shows successful application in automated visual inspection for the quality control of automobile 
valve stem seals. During my post--doctoral work at the Christian Albrechts University Kiel Germany I became familiar 
with geometric computing using the Clifford geometric algebra framework. This opened an unexpectedly and new way of 
seeing and solving problems in applied mathematics, computer science and engineering. During my next years as a 
lecturer and researcher I devoted myself to the development and design of perception action systems. 
I am interested to develop real time algorithms for controlling the perception (vision, laser, omnidirectional, 
ultrasound) and action (planning, relocation, navigation, object manipulation). Within a perception action cycle (PAC) 
our machine should increase its capabilities to recognize relevant categories. Here geometric learning is key for 
the enlargement of its consciousness. We chose for the design of PAC systems the geometric algebra framework system. 
In this system many standard algorithms can be integrated for making the system more robust. Currently we are 
employing modern mathematical formalisms which may elucidate advanced concepts for the assessment and management of 
uncertainty in geometric computations. Goals and benefits of our research will be of a theoretical, practical and 
industrial nature. My publications reflect results in a wide spectrum of related disciplines ranging from basic 
research to real industrial applications. Since the nineties I have actively worked in training MS and PhD students, 
guiding industrial projects and enlarging my own theory of geometric computing for cognitive systems where learning 
plays the key role.

My current theoretical and applied research interests can be categorized as follows:

Basic Research

1.	Geometric neural networks 
2.	Quaternion, Clifforf  Fourier transform and Quaternion, Clifford  Wavelet transform 
3.	Geometry of n uncalibrated cameras (calibration, reconstruction, dynamics) 
4.	Kinematics and dynamics of serial and parallel manipulators 
5.	Mobile robots 
6.	Active vision 
7.	Sensor fusion (ultrasound, laser, stereo binocular systems, omnidirectional systems) 
8.	Learning of spatial-temporal events 
9.	Geometric computing under uncertainty, geometric fuzzy logic 
10.	Bio-robotics
11.	Cognitive robotics
12.	Design of robot systems
13.	Humanoids (cognitive architecture)

Applied research

1.	Intelligent automated visual inspection 
2.	Robots for inspection 
3.	Visual guided robot manipulators for the electronics and car industries 
4.	Service mobile robots 
5.	Computer aided neurosurgery  and laparoscopy (fusion of ultrasound and cameras)
6.	AI robotics for education and rehabilitation 
7.	Computer graphics, virtual reality, visualization 
8.	Programming for geometric computing