41 citations · 99 across the 7 of their papers we have counts for
8 papers
Self-Predictive Representation for Autonomous UAV Object-Goal Navigation
Angel Ayala, Donling Sui, Francisco Cruz +3
Autonomous Unmanned Aerial Vehicles (UAVs) have revolutionized industries through their versatility with applications including aerial surveillance, search and rescue, agriculture,…
How Can LLMs and Knowledge Graphs Contribute to Robot Safety? A Few-Shot Learning Approach
Abdulrahman Althobaiti, Angel Ayala, JingYing Gao +4
Large Language Models (LLMs) are transforming the robotics domain by enabling robots to comprehend and execute natural language instructions. The cornerstone benefits of LLM includ…
Explaining Agent's Decision-making in a Hierarchical Reinforcement Learning Scenario
Hugo Muñoz, Ernesto Portugal, Angel Ayala +2
Reinforcement learning is a machine learning approach based on behavioral psychology. It is focused on learning agents that can acquire knowledge and learn to carry out new tasks b…
Explainable Deep Reinforcement Learning Using Introspection in a Non-episodic Task
Angel Ayala, Francisco Cruz, Bruno Fernandes +1
Explainable reinforcement learning allows artificial agents to explain their behavior in a human-like manner aiming at non-expert end-users. An efficient alternative of creating ex…
Unmanned Aerial Vehicle Control Through Domain-based Automatic Speech Recognition
Ruben Contreras, Angel Ayala, Francisco Cruz
Currently, unmanned aerial vehicles, such as drones, are becoming a part of our lives and reaching out to many areas of society, including the industrialized world. A common altern…
KutralNet: A Portable Deep Learning Model for Fire Recognition
Angel Ayala, Bruno Fernandes, Francisco Cruz +3
Most of the automatic fire alarm systems detect the fire presence through sensors like thermal, smoke, or flame. One of the new approaches to the problem is the use of images to pe…
A Comparison of Humanoid Robot Simulators: A Quantitative Approach
Angel Ayala, Francisco Cruz, Diego Campos +3
Research on humanoid robotic systems involves a considerable amount of computational resources, not only for the involved design but also for its development and subsequent impleme…
Deep Reinforcement Learning with Interactive Feedback in a Human-Robot Environment
Ithan Moreira, Javier Rivas, Francisco Cruz +3
Robots are extending their presence in domestic environments every day, being more common to see them carrying out tasks in home scenarios. In the future, robots are expected to in…