Towards autonomous multi-UAV wireless network: A survey of reinforcement learning-based approaches
Unmanned aerial vehicle (UAV)-based wireless networks have received increasing
research interest in recent years and are gradually being utilized in various aspects of our …
research interest in recent years and are gradually being utilized in various aspects of our …
A review of cooperative multi-agent deep reinforcement learning
A Oroojlooy, D Hajinezhad - Applied Intelligence, 2023 - Springer
Abstract Deep Reinforcement Learning has made significant progress in multi-agent
systems in recent years. The aim of this review article is to provide an overview of recent …
systems in recent years. The aim of this review article is to provide an overview of recent …
Swarm of micro flying robots in the wild
Aerial robots are widely deployed, but highly cluttered environments such as dense forests
remain inaccessible to drones and even more so to swarms of drones. In these scenarios …
remain inaccessible to drones and even more so to swarms of drones. In these scenarios …
Trace and pace: Controllable pedestrian animation via guided trajectory diffusion
We introduce a method for generating realistic pedestrian trajectories and full-body
animations that can be controlled to meet user-defined goals. We draw on recent advances …
animations that can be controlled to meet user-defined goals. We draw on recent advances …
Spatio-temporal graph transformer networks for pedestrian trajectory prediction
Understanding crowd motion dynamics is critical to real-world applications, eg, surveillance
systems and autonomous driving. This is challenging because it requires effectively …
systems and autonomous driving. This is challenging because it requires effectively …
Motion planning and control for mobile robot navigation using machine learning: a survey
Moving in complex environments is an essential capability of intelligent mobile robots.
Decades of research and engineering have been dedicated to developing sophisticated …
Decades of research and engineering have been dedicated to developing sophisticated …
Crowd-robot interaction: Crowd-aware robot navigation with attention-based deep reinforcement learning
Mobility in an effective and socially-compliant manner is an essential yet challenging task for
robots operating in crowded spaces. Recent works have shown the power of deep …
robots operating in crowded spaces. Recent works have shown the power of deep …
Core challenges of social robot navigation: A survey
Robot navigation in crowded public spaces is a complex task that requires addressing a
variety of engineering and human factors challenges. These challenges have motivated a …
variety of engineering and human factors challenges. These challenges have motivated a …
A review of motion planning algorithms for intelligent robots
Principles of typical motion planning algorithms are investigated and analyzed in this paper.
These algorithms include traditional planning algorithms, classical machine learning …
These algorithms include traditional planning algorithms, classical machine learning …
Distributed multi-robot collision avoidance via deep reinforcement learning for navigation in complex scenarios
Developing a safe and efficient collision-avoidance policy for multiple robots is challenging
in the decentralized scenarios where each robot generates its paths with limited observation …
in the decentralized scenarios where each robot generates its paths with limited observation …