Dr. János Botzheim
Budapest University of Technology and Economics, Hungary
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Academic Career Length
26Years (2001-Present)
(Calculated once Scilit publication data is synced: current year − year of first publication + 1)
Representative Publications
View All Publications27 January 2009 in International Journal of Intelligent Systems
Journal Article
János BotzheimCCCristiano Lourenço Cabrita
Cristiano Lourenço Cabrita
Laszlo T. Koczy
Antonio Ruano1 June 2015 in Expert Systems with Applications
Journal Article
DTDalai Tang
Dalai Tang
BYBakhtiar Yusuf
Bakhtiar Yusuf
János BotzheimNKNaoyuki Kubota
Naoyuki KubotaCCChee Seng Chan
Chee Seng Chan10 February 2012 in Memetic Computing
Journal Article
1 December 2015 in IEEE Transactions on Systems, Man, and Cybernetics: Systems
Journal Article
ASAzhar Aulia Saputra
Azhar Aulia SaputraJános BotzheimISIndra Adji Sulistijono
Indra Adji SulistijonoNKNaoyuki Kubota
Naoyuki KubotaThis paper proposes the control system for 3-D locomotion of a humanoid biped robot based on a biological approach. The muscular system in the human body and the neural oscillator for generating locomotion signals are adapted in this paper. We extend the neuro-locomotion system for modeling a multiple neuron system, where motoric neurons represent the muscular system and sensoric neurons represent the sensor system inside the human body. The output signals from coupled neurons representing the angle joint level are controlled by gain neurons that represent the energy burst for driving the joint in each motor. The direction and the length of step in robot locomotion can be adjusted by command neurons. In order to form the locomotion pattern, we apply multiobjective evolutionary computation to solve the multiobjective problem when optimizing synapse weights between the motoric neurons. We use recurrent neural network (RNN) for the stabilization system required for supporting locomotion. RNN generates a dynamic weight synapse value between the sensoric neuron and the motoric neuron. The effectiveness of our system is demonstrated in open dynamic engine computer simulation and in a real robot application that has 12 degrees of freedom (DoFs) in legs and four DoFs in hands.
1 September 2018 in Expert Systems with Applications
Journal Article
TBTamás Bódis
Tamás BódisJános Botzheim26 February 2021 in IEEE Transactions on Cybernetics
Journal Article
ASAzhar Aulia Saputra
Azhar Aulia SaputraJános BotzheimAIAuke Jan Ijspeert
Auke Jan IjspeertNKNaoyuki Kubota
Naoyuki KubotaThis article examines the importance of integrating locomotion and cognitive information for achieving dynamic locomotion from a viewpoint combining biology and ecological psychology. We present a mammalian neuromusculoskeletal model from external sensory information processing to muscle activation, which includes: 1) a visual-attention control mechanism for controlling attention to external inputs; 2) object recognition representing the primary motor cortex; 3) a motor control model that determines motor commands traveling down the corticospinal and reticulospinal tracts; 4) a central pattern generation model representing pattern generation in the spinal cord; and 5) a muscle reflex model representing the muscle model and its reflex mechanism. The proposed model is able to generate the locomotion of a quadruped robot in flat and natural terrain. The experiment also shows the importance of a postural reflex mechanism when experiencing a sudden obstacle. We show the reflex mechanism when a sudden obstacle is separately detected from both external (retina) and internal (touching afferent) sensory information. We present the biological rationale for supporting the proposed model. Finally, we discuss future contributions, trends, and the importance of the proposed research.
About Me
Janos Botzheim has an M.Sc. in Technical Informatics (2001) and a Ph.D. in Computer Engineering (2008) from the Budapest University of Technology and Economics. He joined the Department of Automation at Szechenyi Istvan University, Gyor, Hungary, in 2007 as a senior lecturer, in 2008 as an assistant professor, and in 2009 as an associate professor. He was a visiting researcher at the Graduate School of Systems Design of Tokyo Metropolitan University from September 2010 to March 2011 and from September 2011 to February 2012. He was an associate professor at the Graduate School of Systems Design at Tokyo Metropolitan University from April 2012 to March 2017. He was an associate professor in the Department of Mechatronics, Optics and Mechanical Engineering Informatics at the Budapest University of Technology and Economics from February 2018 to August 2021. He has been the Head of the Department of Artificial Intelligence at Eötvös Loránd University, Faculty of Informatics, Budapest, Hungary, since September 2021. His research interests include computational intelligence, memetic algorithms, applications of computational intelligence in robotics, and cognitive robotics. He is a member of the following scientific societies: the John von Neumann Computer Society, Hungarian Academy of Engineering, Hungarian Fuzzy Association, IEEE, IEEE Computational Intelligence Society, IEEE Robotics and Automation Society, IEEE Systems, Man, and Cybernetics Society, and IEEE Computer Society.