Effective deep reinforcement learning setups for multiple goals on visual navigation (2020)
- Authors:
- USP affiliated authors: WOLF, DENIS FERNANDO - ICMC ; GRASSI JUNIOR, VALDIR - EESC ; HORITA, LUIZ RICARDO TAKESHI - ICMC
- Unidades: ICMC; EESC
- DOI: 10.1109/IJCNN48605.2020.9206917
- Subjects: ALGORITMOS; REDES NEURAIS
- Keywords: reinforcement learning; goal-driven navigation; visual navigation
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Publisher: IEEE
- Publisher place: Piscataway
- Date published: 2020
- Source:
- Título: Proceedings
- Conference titles: International Joint Conference on Neural Networks - IJCNN
- Este periódico é de assinatura
- Este artigo NÃO é de acesso aberto
- Cor do Acesso Aberto: closed
-
ABNT
HORITA, Luiz Ricardo Takeshi e WOLF, Denis Fernando e GRASSI JÚNIOR, Valdir. Effective deep reinforcement learning setups for multiple goals on visual navigation. 2020, Anais.. Piscataway: IEEE, 2020. Disponível em: https://doi.org/10.1109/IJCNN48605.2020.9206917. Acesso em: 27 dez. 2025. -
APA
Horita, L. R. T., Wolf, D. F., & Grassi Júnior, V. (2020). Effective deep reinforcement learning setups for multiple goals on visual navigation. In Proceedings. Piscataway: IEEE. doi:10.1109/IJCNN48605.2020.9206917 -
NLM
Horita LRT, Wolf DF, Grassi Júnior V. Effective deep reinforcement learning setups for multiple goals on visual navigation [Internet]. Proceedings. 2020 ;[citado 2025 dez. 27 ] Available from: https://doi.org/10.1109/IJCNN48605.2020.9206917 -
Vancouver
Horita LRT, Wolf DF, Grassi Júnior V. Effective deep reinforcement learning setups for multiple goals on visual navigation [Internet]. Proceedings. 2020 ;[citado 2025 dez. 27 ] Available from: https://doi.org/10.1109/IJCNN48605.2020.9206917 - Improving multi-goal and target-driven reinforcement learning with supervised auxiliary task
- Identificação do modelo longitudinal de um veículo de grande porte utilizando processos gaussianos
- Detecção de vagas e estacionamento autônomo de veículos
- Obstacle avoidance using stereo-based generic obstacle tracking
- Autonomous vehicle navigation in semi-structured urban environment
- Decision making for autonomous vehicles at signalized intersection under uncertain traffic signal phase and timing information
- Longitudinal and lateral control for autonomous ground vehicles
- An effective combination of loss gradients for multi-task learning applied on instance segmentation and depth estimation
- Leveraging convergence behavior to balance conflicting tasks in multitask learning
- Fast visual road recognition and horizon detection using multiple artificial neural networks
Informações sobre o DOI: 10.1109/IJCNN48605.2020.9206917 (Fonte: oaDOI API)
Download do texto completo
| Tipo | Nome | Link | |
|---|---|---|---|
 |
3007469.pdf |
How to cite
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
