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Aldo-Jonathan Munoz-Vazquez

dblp:135/8517 · also Aldo-Jonathan Muñoz-Vázquez · DBLP profile ↗
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6ranked-venue papers
1as first author
5since 2021 · last 2023
0000-0001-5125-2644ORCID · verified

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 5 · 1 first-author · 4 since 2021Systems, architecture and hardware · 3 · 1 first-author · 2 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Artificial intelligence
1 paper
Motion planning and robot control · 67% Video understanding and tracking · 33%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Computer vision › Video understanding and tracking › object tracking
contour tracking
0.212013
Passive Velocity Field Control for contour tracking of robots with model-free controller · ICRA 2013
Robotics › Motion planning and robot control
robot control
0.212013
Passive Velocity Field Control for contour tracking of robots with model-free controller · ICRA 2013
Robotics › Motion planning and robot control › robot control
sliding mode control
0.212013
Passive Velocity Field Control for contour tracking of robots with model-free controller · ICRA 2013

Methods — techniques the papers use, named apart from their topics

lyapunov stability · 0.2fuzzy aggregation · 0.2
YearPublicationVenuePosition
2023 Optimal drug-dosing of cancer dynamics with fuzzy reinforcement learning and discontinuous reward function
Chidentree Treesatayapun, Aldo-Jonathan Munoz-Vazquez
Eng. Appl. Artif. Intell.2
2023 Synchronization of fractional-order chaotic networks in Presnov form via homogeneous controllers
Oscar Martinez-Fuentes, Aldo-Jonathan Munoz-Vazquez, Guillermo Fernández-Anaya, Esteban Tlelo-Cuautle
Integr.2
2023 Reinforcement control with fuzzy-rules emulated network for robust-optimal drug-dosing of cancer dynamics
Chidentree Treesatayapun, Aldo-Jonathan Munoz-Vazquez
Neural Comput. Appl.2
2023 Reinforcement learning optimal control with semi-continuous reward function and fuzzy-rules networks for drug administration of cancer treatment
Chidentree Treesatayapun, Aldo-Jonathan Munoz-Vazquez, Naret Suyaroj
Soft Comput.2
2022 Stabilization of Tangent and Normal Contact Forces for a Quadrotor subject to Disturbances
abstract
Force exertion, object manipulation, and interaction are novel trending research topics of autonomous flying robots that can yield hoovering. Moreover, specifically with quadrotors, the vibration caused by the high natural frequency of rotating propellers exacerbates the problem of maintaining contact and exerting force against a rigidly fixed object. This contact vibration transfers back kinetic energy to the quadrotor that, in worst-case scenarios, surpasses its flying capabilities, which may lead to a crash. This paper studies the problem of aerial contact stabilization of a quadrotor equipped with a hemispherical deformable tip, which accommodates contact forces at a lower frequency. Thus two phenomena not studied in the literature arise: the rolling motion, and the deformation at contact. The contact force stabilization restores the effects of deformation while simultaneously endowing rolling by controlling a tangent constrained force. A model-free continuous attitude fractional controller to guarantee finite-time attitude stabilization is proposed. The residual coupled nonlinear dynamics yields the desired attitude corresponding to a given contact force; thus, force stabilization is achieved. Finally, experimental results are presented to assess the performance of the proposed approach.
Carlos Izaguirre, Aldo-Jonathan Munoz-Vazquez, Anand Sánchez-Orta, Vicente Parra-Vega, Rodolfo García-Rodríguez, Pedro Castillo, Daniel Arreguín-Jasso
IROS2
2013 Passive Velocity Field Control for contour tracking of robots with model-free controller
abstract
A simple, fast and robust Passive Velocity Field Control (PVFC) scheme for contour tracking in 2D and 3D is presented. A model-free and chattering-free second order sliding mode controller is proposed, which enforces an invariant manifold for all time such that the generalized velocity tracks the spatial velocity field. A constructive simple and intuitive method to design this velocity field is built upon a fuzzy aggregation of orthogonal vectors to guide the end-effector subject to a dissipative map. Stability properties in the sense of Lyapunov establish the fast and yet smooth tracking with typical robustness of sliding modes. In this way, the closed-loop system exhibits the mildness of PVFC but it evades the subtle complexities of the original approach PVFC. A simulation study is discussed, and experimental results highlight the characteristics of the proposed approach.
Aldo-Jonathan Munoz-Vazquez, Vicente Parra-Vega, Anand Sánchez-Orta, Octavio García 0001, Francisco José Ruiz Sanchez, Sergio Rosales
ICRA1