activity
20192023
most citedA Survey on Offline Reinforcement Learning: Taxonomy, Review, and Open Problems

339 citations · 408 across the 13 of their papers we have counts for

collaborators

13 papers

cs.RO2023★ 3 cited

A Mixed-Integer Approach for Motion Planning of Nonholonomic Robots under Visible Light Communication Constraints

Angelo Caregnato-Neto, Marcos Ricardo Omena de Albuquerque Maximo, Rubens Junqueira Magalhães Afonso

This work addresses the problem of motion planning for a group of nonholonomic robots under Visible Light Communication (VLC) connectivity requirements. In particular, we consider…

cs.CV2023★ 26 cited

Transformer-Based Model for Monocular Visual Odometry: A Video Understanding Approach

André O. Françani, Marcos R. O. A. Maximo

Estimating the camera's pose given images from a single camera is a traditional task in mobile robots and autonomous vehicles. This problem is called monocular visual odometry and…

cs.RO2023★ 1 cited

Autonomous Agent for Beyond Visual Range Air Combat: A Deep Reinforcement Learning Approach

Joao P. A. Dantas, Marcos R. O. A. Maximo, Takashi Yoneyama

This work contributes to developing an agent based on deep reinforcement learning capable of acting in a beyond visual range (BVR) air combat simulation environment. The paper pres…

cs.CV2022★ 11 cited

Dense Prediction Transformer for Scale Estimation in Monocular Visual Odometry

André O. Françani, Marcos R. O. A. Maximo

Monocular visual odometry consists of the estimation of the position of an agent through images of a single camera, and it is applied in autonomous vehicles, medical robots, and au…

cs.LG2022

Supervised Machine Learning for Effective Missile Launch Based on Beyond Visual Range Air Combat Simulations

Joao P. A. Dantas, Andre N. Costa, Felipe L. L. Medeiros +3

This work compares supervised machine learning methods using reliable data from constructive simulations to estimate the most effective moment for launching missiles during air com…

cs.RO2022★ 14 cited

Real-time motion planning and decision-making for a group of differential drive robots under connectivity constraints using robust MPC and mixed-integer programming

Angelo Caregnato-Neto, Marcos Ricardo Omena de Albuquerque Maximo, Rubens Junqueira Magalhães Afonso

This work is concerned with the problem of planning trajectories and assigning tasks for a Multi-Agent System (MAS) comprised of differential drive robots. We propose a multirate h…