Francisco Quiroga

Pontificia Universidad Católica de Valparaíso

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About

Francisco Quiroga is at the forefront of intelligent robotics, specializing in the application of deep reinforcement learning (DRL) to autonomous navigation and environmental robotics. His research masterfully bridges the critical gap between simulation and reality, a challenge known as Sim2Real. Quiroga’s foundational work, "Position Control of a Mobile Robot through Deep Reinforcement Learning" (2022, 23 citations), established a robust framework for training agents in virtual environments using OpenAI Gym and CoppeliaSim, enabling precise control of simulated robots. Building on this, his most recent and impactful contribution, "RL-Based Sim2Real Enhancements for Autonomous Beach-Cleaning Agents" (2024), demonstrates a significant leap forward. In this work, Quiroga successfully transfers DRL navigation policies from simulation to physical beach-cleaning robots, achieving effective autonomy in real-world, unstructured environments. This achievement not only showcases his technical prowess in reinforcement learning but also highlights a tangible application for environmental sustainability. With a growing citation record, Quiroga is establishing himself as a key innovator in practical, deployable robotic intelligence.