Afonso Vale — accepted AI-conference papers

2025

Enhancing UAV Energy Efficiency and Versatility through Trimodal Ground, Hovering, and Fixed-Wing Locomotion Modes

Afonso Vale, Meysam Basiri, Frederico Afonso

IROS 2025

Multimodal Unmanned Aerial Vehicles (UAVs), capable of operating in different locomotion modes, offer greater versatility and optimized energy usage. This paper presents a novel trimodal UAV that integrates ground locomotion, hovering, and fixed-wing flight using a shared actuator system. The design

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2025

Multitask Reinforcement Learning for Quadcopter Attitude Stabilization and Tracking using Graph Policy

Yu Tang Liu, Afonso Vale, Aamir Ahmad, Rodrigo M. M. Ventura, Meysam Basiri

IROS 2025

Quadcopter attitude control involves two tasks: smooth attitude tracking and aggressive stabilization from arbitrary states. Although both can be formulated as tracking problems, their distinct state spaces and control strategies complicate a unified reward function. We propose a multitask deep rein

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