5 papers
D3D-GEN: Robot-Aware Domain-Grounded Interactive 3D World Generation for Social Robotics
Anh Duc Do, Volodymyr Shcherbyna, Tai Duc Nguyen +5
Training and validation of Embodied AI for social navigation critically depends on realistic simulation environments, yet many current approaches fail to find a balance between rea…
GROVE: Grounded Pedestrian Simulation via Natural Language for Interactive Social Robot Navigation
Duc Tai Nguyen, Volodymyr Shcherbyna, Anh Do Duc +3
Pedestrian simulation is a critical component for training and deploying social robot navigation approaches, yet it remains a largely rigid system that repeatedly requires manual d…
All-in-One: A DRL-based Control Switch Combining State-of-the-art Navigation Planners
Linh Kästner, Johannes Cox, Teham Buiyan +1
Autonomous navigation of mobile robots is an essential aspect in use cases such as delivery, assistance or logistics. Although traditional planning methods are well integrated into…
Connecting Deep-Reinforcement-Learning-based Obstacle Avoidance with Conventional Global Planners using Waypoint Generators
Linh Kästner, Teham Buiyan, Xinlin Zhao +3
Deep Reinforcement Learning has emerged as an efficient dynamic obstacle avoidance method in highly dynamic environments. It has the potential to replace overly conservative or ine…
Arena-Rosnav: Towards Deployment of Deep-Reinforcement-Learning-Based Obstacle Avoidance into Conventional Autonomous Navigation Systems
Linh Kästner, Teham Buiyan, Xinlin Zhao +3
Recently, mobile robots have become important tools in various industries, especially in logistics. Deep reinforcement learning emerged as an alternative planning method to replace…