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 …

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

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

" Embodied visual navigation" problem requires an agent to navigate in a 3D environment
mainly rely on its first-person observation. This problem has attracted rising attention in …

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 …

Autonomous driving presents unique challenges, particularly in transferring agents trained
in simulation to real-world environments due to the discrepancies between the two. To …