Zobrazeno 1 - 10
of 135
pro vyhledávání: '"Brito, Bruno"'
Autor:
Lodel, Max, Brito, Bruno, Serra-Gómez, Álvaro, Ferranti, Laura, Babuška, Robert, Alonso-Mora, Javier
Search missions require motion planning and navigation methods for information gathering that continuously replan based on new observations of the robot's surroundings. Current methods for information gathering, such as Monte Carlo Tree Search, are c
Externí odkaz:
http://arxiv.org/abs/2203.02381
Autor:
de Vries, Jitske, Trevisan, Elia, van der Toorn, Jules, Das, Tuhin, Brito, Bruno, Alonso-Mora, Javier
Publikováno v:
2022 International Conference on Robotics and Automation (ICRA)
In unstructured urban canals, regulation-aware interactions with other vessels are essential for collision avoidance and social compliance. In this paper, we propose a regulations aware motion planning framework for Autonomous Surface Vessels (ASVs)
Externí odkaz:
http://arxiv.org/abs/2202.12069
Autonomous mobile robots require accurate human motion predictions to safely and efficiently navigate among pedestrians, whose behavior may adapt to environmental changes. This paper introduces a self-supervised continual learning framework to improv
Externí odkaz:
http://arxiv.org/abs/2202.07606
In this paper, we present a decentralized and communication-free collision avoidance approach for multi-robot systems that accounts for both robot localization and sensing uncertainties. The approach relies on the computation of an uncertainty-aware
Externí odkaz:
http://arxiv.org/abs/2201.04012
Autor:
Ferreira, Ariela Mota, Oliveira-da Silva, Léa Campos, Cardoso, Clareci Silva, Oliveira, Cláudia Di Lorenzo, Brito, Bruno Oliveira de Figueiredo, Bierrenbach, Ana Luiza, Santos, Ana Clara de Jesus, Cruz, Dardiane Santos, Leite, Sâmara Fernandes, Jesus, Andréia Brito, Damasceno, Renata Fiúza, Nunes, Maria Carmo Pereira, Molina, Israel, Haikal, Desirée Sant’ Anna, Sabino, Ester Cerdeira, Ribeiro, Antonio Luiz Pinho
Publikováno v:
In Travel Medicine and Infectious Disease September-October 2024 61
Autor:
Brito, Bruno José da Silva
Tese de mestrado integrado. Engenharia Electrotécnica e de Computadores (Major Automação). Faculdade de Engenharia. Universidade do Porto. 2009
Externí odkaz:
http://hdl.handle.net/10216/58273
Autonomous navigation in dense traffic scenarios remains challenging for autonomous vehicles (AVs) because the intentions of other drivers are not directly observable and AVs have to deal with a wide range of driving behaviors. To maneuver through de
Externí odkaz:
http://arxiv.org/abs/2107.04538
Robotic navigation in environments shared with other robots or humans remains challenging because the intentions of the surrounding agents are not directly observable and the environment conditions are continuously changing. Local trajectory optimiza
Externí odkaz:
http://arxiv.org/abs/2102.13073
This paper presents a data-driven decentralized trajectory optimization approach for multi-robot motion planning in dynamic environments. When navigating in a shared space, each robot needs accurate motion predictions of neighboring robots to achieve
Externí odkaz:
http://arxiv.org/abs/2102.05382
This paper presents a method for local motion planning in unstructured environments with static and moving obstacles, such as humans. Given a reference path and speed, our optimization-based receding-horizon approach computes a local trajectory that
Externí odkaz:
http://arxiv.org/abs/2010.10190