activity
20222025
most citedGeneralization in Deep Reinforcement Learning for Robotic Navigation by Reward Shaping

53 citations · 60 across the 6 of their papers we have counts for

collaborators

6 papers

eess.SY2025

Guaranteed Time Control using Linear Matrix Inequalities

Víctor Costa da Silva Campos, Mariella Maia Quadros, Luciano Frezzato +2

This paper presents a synthesis approach aiming to guarantee a minimum upper-bound for the time taken to reach a target set of non-zero measure that encompasses the origin, while t…

eess.SY2025

Less Conservative Adaptive Gain-scheduling Control for Continuous-time Systems with Polytopic Uncertainties

Ariany C. Oliveira, Victor C. S. Campos, Leonardo. A. Mozelli

The synthesis of adaptive gain-scheduling controller is discussed for continuous-time linear models characterized by polytopic uncertainties. The proposed approach computes the con…

eess.SY2024★ 2 cited

A New Control Law for TS Fuzzy Models: Less Conservative LMI Conditions by Using Membership Functions Derivative

Leonardo Amaral Mozelli, Victor Costa da Silva Campos

This note proposes a new type of Parallel Distributed Controller (PDC) for Takagi-Sugeno (TS) fuzzy models. Our idea consists of using two control terms based on state feedback, on…

eess.SY2023★ 4 cited

Improving the Design of Linear Controllers for Homogeneous Platooning under Disturbances

Emerson A. da Silva, Leonardo A. Mozelli, Armando A. Neto +1

This paper addresses the problem of longitudinal platooning control of homogeneous vehicles subject to external disturbances, such as wind gusts, road slopes, and parametric uncert…

cs.RO2022★ 53 cited

Generalization in Deep Reinforcement Learning for Robotic Navigation by Reward Shaping

Victor R. F. Miranda, Armando A. Neto, Gustavo M. Freitas +1

In this paper, we study the application of DRL algorithms in the context of local navigation problems, in which a robot moves towards a goal location in unknown and cluttered works…

eess.SY2022★ 1 cited

Robust Longitudinal Control for Vehicular Autonomous Platoons Using Deep Reinforcement Learning

Armando Alves Neto, Leonardo Amaral Mozelli

In the last few years, researchers have applied machine learning strategies in the context of vehicular platoons to increase the safety and efficiency of cooperative transportation…