Gabriel Alexis Guijarro Reyes was born in Torreon, Coahuila, Mexico in 1995. He obtained his B.S. in Mechatronics and Process Control Systems Engineering in 2018 at Universidad La Salle Laguna, Gomez Palacio, Durango, Mexico . He is currently studying a M.S. in Computer Science at Texas A&M University Corpus Christi under Dr. Luis Rodolfo Garcia Carrillo and Dr. Scott A. King supervision.
My research fields are:
DNN for Human Gesture-Triggered Action Control applied to UAS
Title: Deep Neural Network-Inspired Approach for Human Gesture-Triggered Action Control applied to Unmanned Aircraft Systems
Authors: Gabriel Alexis Guijarro Reyes, Juan Martinez, Luis Rodolfo Garcia Carrillo, Ignacio Rubio Scola, Scott A. King, and Jose Baca.
Abstract: Deep Neural Networks have positively impacted the development of autonomous navigation strategies, allowing the integration of object detection capabilities to the vast array of already existing control methods. In this project, a Deep Neural Network is implemented to distinguish particular hand gestures, as well as user's arm movement, in order to trigger a specific activity of an Unmanned Aircraft System. We present real-time experimental results of how this technique is applied, making use of a Natural User Interface to control a the autonomous aircraft.
Experiment with a leader and a follower UAS
Experiment with an object as leader and a follower UAS
Title: A Geometric Control Strategy for Real-time Coordination of Multiple Unmanned Aircraft Systems
Authors: Gabriel Alexis Guijarro Reyes, Luis Rodolfo Garcia Carrillo and Pablo Rangel.
Abstract: In recent years, the application of Unmanned Aircraft Systems (UAS) has incremented due to their cost-effectiveness ratio, portability and reduced size. This allows their utilization in multiple operations in complex military and civilian applications. UAS operations sometimes require the usage of human pilots to manage the different situations that can be present at any moment of a mission, and to decide the better option for every UAS involved. The simplest way to realize these tasks is to gather multiple pilots, one for each UAS. However, this option carries the complexity of coordinating the actions of every pilot involved in the mission. This might require several hours of specialized training, delays, and higher costs. To mitigate these nuances, this paper proposes a geometric control method to stabilize multiple UAS in formation. Our method allows a group of UAS to accomplish tasks using a determined formation. Two experiments are presented that demonstrates the performance of the technique. In the first experiment, one UAS is configured as a leader, while a second UAS is configured as a follower. The second experiment considers a scenario where the leader UAS is replaced by a physical device that can be used by a non-trained human pilot to directly affect the behavior of the follower UAS.
[1] I. Rubio Scola, G.A. Guijarro Reyes, L. R. Garcia Carrillo, J. Hespanha and J. Xie, “Translational Model Identification and Robust Control for the Parrot Mambo UAS Multicopter” To appear in IEEE Globecom Workshop on Computing Centric Drone Networks, Hawaii, USA, December 2019. (To be published)
[2] G.A. Guijarro Reyes, L.R. Garcia Carrillo, I. Rubio Scola, J. Martinez, J. Baca, and S.King, “Human gesture-triggered control actions for Unmanned Aircraft Systems: A Deep Neural Network-Inspired Approach”, Latin American Congress on Automation and Robotics (LACAR), Cali, Colombia, November 2019. [DOI]
[3] B. Wang, J. Xie, Y. Wan, G.A. Guijarro Reyes, and L.R. Garcia Carrillo, “3-D Trajectory Modeling for Unmanned Aerial Vehicles”, AIAA Science and Technology Forum and Exposition, January 2019, San Diego CA, USA. [DOI]
[4] G.A. Guijarro Reyes, L.R. Garcia Carrillo, and P. Rangel. “A Geometric Control Strategy for Real-Time Coordination of Multiple Unmanned Aircraft Systems”, 2018 International Conference on Unmanned Aircraft Systems, June 2018, Dallas, TX, USA. [DOI]