There is an increasing demand for using Unmanned Aerial Vehicle (UAV), known as drones,
in different applications such as packages delivery, traffic monitoring, search and rescue …

Purely MLP-based neural radiance fields (NeRF-based methods) often suffer from
underfitting with blurred renderings on large-scale scenes due to limited model capacity …

With the recent development of deep learning technology comes the wide use of artificial
intelligence (AI) models in various domains. AI shows good performance for definite …

Intelligent systems are increasingly part of our everyday lives and have been integrated
seamlessly to the point where it is difficult to imagine a world without them. Physical …

Reinforcement learning (RL) is effective for autonomous navigation tasks without prior
knowledge of the environment. However, traditional mobile robot navigation algorithms …

With the recent development of deep learning, AI models are widely used in various
domains. AI models show good performance for definite tasks such as image classification …

We introduce an automatic curriculum algorithm, Variational Automatic Curriculum Learning
(VACL), for solving challenging goal-conditioned cooperative multi-agent reinforcement …

Existing deep reinforcement learning-based mobile robot navigation relies largely on single-
modal visual perception to perform local-scale navigation. However, multimodal visual …

Collaborative autonomous landing of a quadrotor Unmanned Aerial Vehicle (UAV) on a
moving Unmanned Ground Vehicle (UGV) presents challenges due to the need for accurate …

We propose a deep reinforcement learning approach for solving a mapless navigation
problem in warehouse scenarios. In our approach, an automatic guided vehicle is equipped …